Yi Wang (0000-0002-1280-5418)

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I received the Ph.D. degree from the Department of Electrical and Electronic Engineering at Imperial College London, U.K., in 2022. I am currently employed as a Research Associate in the Department of Electrical and Electronic Engineering at Imperial College London. My research interests include mathematical programming and learning approaches applied to resilient power system operation and planning, multi-energy system integration, and the voltage regulation of active distribution networks.

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Imperial College London: London, GB

Research associate (Electrical and Electronic Engineering)

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Yi Wang

https://orcid.org/0000-0002-1280-5418

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Employment (1)

Imperial College London: London, GB

Works (26)

Regional Frequency-Constrained Planning for the Optimal Sizing of Power Systems Via Enhanced Input Convex Neural Networks

Co-optimising frequency-containment services from zero-carbon sources in electricity grids dominated by Renewable Energy Sources

Resilient energy management of a multi-energy building under low-temperature district heating: A deep reinforcement learning approach

Coordinating Multi-Energy Microgrids for Integrated Energy System Resilience: A Multi-Task Learning Approach

Graph Reinforcement Learning for Carbon-Aware Electric Vehicles in Power-Transport Networks

Transient Stability-Driven Planning for the Optimal Sizing of Resilient AC/DC Hybrid Microgrids

Artificial Intelligence for Microgrid Resilience: A Data-Driven and Model-Free Approach

A resilience-oriented pre-positioning approach for electric vehicle routing and scheduling in coupled energy and transport sectors

Decarbonising the GB Power System via Numerous Electric Vehicle Coordination

Market design for ancillary service provisions of inertia and frequency response via virtual power plants: A non-convex bi-level optimisation approach

Resilience-Oriented Coordination of Networked Microgrids: A Shapley Q-Value Learning Approach

Graph Learning-Based Voltage Regulation in Distribution Networks With Multi-Microgrids

Towards Microgrid Resilience Enhancement via Mobile Power Sources and Repair Crews: A Multi-Agent Reinforcement Learning Approach

Multi-agent reinforcement learning for electric vehicle decarbonized routing and scheduling

Personalized retail pricing design for smart metering consumers in electricity market

A stochastic distributed control approach for load restoration of networked microgrids with mobile energy storage systems

Hierarchical multi-agent reinforcement learning for repair crews dispatch control towards multi-energy microgrid resilience

Reinforcement learning for electric vehicle applications in power systems:A critical review

Coordinated Electric Vehicle Active and Reactive Power Control for Active Distribution Networks

Hybrid Multiagent Reinforcement Learning for Electric Vehicle Resilience Control Towards a Low-Carbon Transition

Multi-service provision for electric vehicles in power-transportation networks towards a low-carbon transition: A hierarchical and hybrid multi-agent reinforcement learning approach

Multi-agent deep reinforcement learning for resilience-driven routing and scheduling of mobile energy storage systems

A Three-Level Planning Model for Optimal Sizing of Networked Microgrids Considering a Trade-Off Between Resilience and Cost

A resilience enhancement strategy for networked microgrids incorporating electricity and transport and utilizing a stochastic hierarchical control approach

On microgrids and resilience: A comprehensive review on modeling and operational strategies

Resilience-Driven Modeling, Operation and Assessment for a Hybrid AC/DC Microgrid

Peer review (35 reviews for 14 publications/grants)