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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
Published:
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portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Optimum Design of Battery-Assisted Photo-Voltaic Energy System for a Commercial Application
Published in IEEE Power & Energy Society General Meeting (PESGM), 2019
Before commercial users purchase and install the PV system, do they have an idea of how much to spend on it? And what is the break even point of the system? This short paper models this optimization problem.
Recommended citation: Y. Li and J. Wu, “Optimum design of battery-assisted photo-voltaic energy system for a commercial application,” in Power & Energy Society General Meeting (PESGM). IEEE, 2019. https://ieeexplore.ieee.org/abstract/document/8973467
Optimum Integration of Solar Energy With Battery Energy Storage Systems
Published in IEEE Transactions on Engineering Management, 2020
The entire life cycles of solar panels and BESS of the order of ten years or longer, makes the complexity of MILP very high. A dynamic programming approach is given in this paper.
Recommended citation: Y. Li and J. Wu, “Optimum integration of solar energy with battery energy storage systems,” IEEE Transactions on Engineering Management, 2020. https://ieeexplore.ieee.org/abstract/document/9019606
Multi-user Multi-channel Computation Offloading and Resource Allocation for Mobile Edge Computing
Published in IEEE International Conference on Communications (ICC), 2020
The problem of computation offloading and resourceallocation in multi-user multi-channel mobile edge computing (MEC) systems is to minimize a cost function that is expressed as a weighted sum of energy consumption, delay, and deadline penalty of all user equipments (UEs). A Deep Reinforcement Learning approach known as Deep Deterministic Policy Gradient (DDPG) is applied.
Recommended citation: S. Nath, Y. Li, J. Wu, and P. Fan, “Multi-user multi-channel computation offloading and resource allocation for mobile edge computing,” in ICC 2020-2020 IEEE International Conference on Communications (ICC). IEEE, 2020, pp. 1–6. https://ieeexplore.ieee.org/abstract/document/9149124
Low Latency Cyberattack Detection in Smart Grids with Deep Reinforcement Learning
Published in International Journal of Electrical Power & Energy Systems, 2022
Traditional detection methods of cyberattacks in smart grids focus mainly on detection accuracy and pay little attention to detection delay. While a lower detection delay can reduce recovery time, thus minimizing service interruption or economic losses due to cyberattacks. This paper proposed a redinforcement learning based detection algorithm that achieve very low detection delays with high detection accuracy.
Recommended citation: Y. Li and J. Wu, “Low latency cyberattack detection in smart grids with deep reinforcement learning,” International Journal of Electrical Power & Energy Systems, vol. 142, p. 108265, 2022. https://www.sciencedirect.com/science/article/abs/pii/S0142061522002897
Low Latency Attack Detection with Dynamic Watermarking for Grid-Connected Photovoltaic Systems
Published in International Journal of Electrical Power & Energy Systems, 2023
The grid-connected photovoltaic (PV) systems under attack will effect the cybersecurity of the smart grids. A quick detection algorithm is developed by using a hybrid model- and data-driven approach, where the test statistics are formulated by using both the physical model of the PV farm and historical measurements.
Recommended citation: Y. Li, N. Lin, J. Wu, Y. Pan and Y. Zhao, "Low Latency Attack Detection with Dynamic Watermarking for Grid-Connected Photovoltaic Systems," in IEEE Journal of Emerging and Selected Topics in Industrial Electronics, doi: 10.1109/JESTIE.2023.3327051 https://ieeexplore.ieee.org/abstract/document/10304585
Deep Reinforcement Learning for Online Scheduling of Photovoltaic Systems with Battery Energy Storage Systems
Published in Intelligent and Converged Networks, 2024
The dynamic programming approach for battery schedule has less complexity but is still an off-line optimization which users can not directly apply to their solar panels. Is there a way to use the schedule strategy while running the solar system?
Recommended citation: Y. Li, J. Wu and Y. Pan, "Deep Reinforcement Learning for Online Scheduling of Photovoltaic Systems with Battery Energy Storage Systems," in Intelligent and Converged Networks, vol. 5, no. 1, pp. 28-41, March 2024, doi: 10.23919/ICN.2024.0003 https://ieeexplore.ieee.org/abstract/document/10484537
talks
Talk 1 on Relevant Topic in Your Field
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.