1 code implementation • 2 Feb 2018 • Yize Chen, Pan Li, Baosen Zhang
We present a method to generate renewable scenarios using Bayesian probabilities by implementing the Bayesian generative adversarial network~(Bayesian GAN), which is a variant of generative adversarial networks based on two interconnected deep neural networks.
no code implementations • 13 Mar 2017 • Hossein Hosseini, Yize Chen, Sreeram Kannan, Baosen Zhang, Radha Poovendran
Advances in Machine Learning (ML) have led to its adoption as an integral component in many applications, including banking, medical diagnosis, and driverless cars.
no code implementations • 20 Sep 2018 • Yize Chen, Hao Wang
The prosperity of smart mobile devices has made mobile crowdsensing (MCS) a promising paradigm for completing complex sensing and computation tasks.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 13 Mar 2019 • Congmei Jiang, Yize Chen, Yongfang Mao, Yi Chai, Mingbiao Yu
In order to minimize the decision risks in power systems with large amount of renewable resources, there is a growing need to model the short-term generation uncertainty.
no code implementations • 18 Oct 2021 • Alexander Pan, Yongkyun Lee, huan zhang, Yize Chen, Yuanyuan Shi
Due to the proliferation of renewable energy and its intrinsic intermittency and stochasticity, current power systems face severe operational challenges.
no code implementations • 30 Nov 2021 • Yize Chen, Yuanyuan Shi, Daniel Arnold, Sean Peisert
Fast and safe voltage regulation algorithms can serve as fundamental schemes for achieving a high level of renewable penetration in the modern distribution power grids.
no code implementations • 27 Jan 2022 • Daniel Arnold, Sy-Toan Ngo, Ciaran Roberts, Yize Chen, Anna Scaglione, Sean Peisert
Volt-VAR and Volt-Watt control functions are mechanisms that are included in distributed energy resource (DER) power electronic inverters to mitigate excessively high or low voltages in distribution systems.
no code implementations • 27 Nov 2022 • Yufan Zhang, Honglin Wen, Tao Feng, Yize Chen
Numerical studies demonstrate compared with the benchmarking strategy, the proposed approach can reduce the price to the reference point with less efforts in demand reduction.
no code implementations • 1 Dec 2022 • Xuan He, Honglin Wen, Yufan Zhang, Yize Chen
Unit commitment (UC) are essential tools to transmission system operators for finding the most economical and feasible generation schedules and dispatch signals.
no code implementations • 16 Feb 2023 • Ruohong Liu, Yize Chen
Deployment of shared energy storage systems (SESS) allows users to use the stored energy to meet their own energy demands while saving energy costs without installing private energy storage equipment.
no code implementations • 29 Jun 2023 • Ruohong Liu, Yuxin Pan, Yize Chen
Demand flexibility plays a vital role in maintaining grid balance, reducing peak demand, and saving customers' energy bills.
no code implementations • ICCV 2023 • Haotian Bai, Yiqi Lin, Yize Chen, Lin Wang
The explicit neural radiance field (NeRF) has gained considerable interest for its efficient training and fast inference capabilities, making it a promising direction such as virtual reality and gaming.
no code implementations • 12 Sep 2023 • Xuan He, Jiayu Tian, Yufan Zhang, Honglin Wen, Yize Chen
Extensive simulations on both specific load samples and load regions validate the proposed technique can screen out more than 80% constraints while preserving the feasibility of multi-interval UC problem.
no code implementations • 11 Dec 2023 • Xuan He, Danny H. K. Tsang, Yize Chen
In this paper, we propose a novel planning and operation model minimizing the system-level carbon emissions via sitting and operating geographically shiftable resources.
no code implementations • 18 Feb 2024 • Yuqi Jiang, Yan Li, Yize Chen
Though the strong capabilities of learning the non-linearity of the load patterns and the high prediction accuracy have been achieved, the interpretability of typical deep learning models for electricity load forecasting is less studied.
no code implementations • 16 Apr 2024 • Chengyang Gu, Yuxin Pan, Ruohong Liu, Yize Chen
Thus, to model and optimize EV charging, it is important for charging station operator to model the PBDR patterns of EV customers by precisely predicting charging demands given price signals.
1 code implementation • 7 Nov 2017 • Yize Chen, Xiyu Wang, Baosen Zhang
Simulation results indicate our method is able to generate scenarios that capture spatial and temporal correlations.
Optimization and Control
1 code implementation • 15 Jun 2020 • Yize Chen, Weiwei Yang, Baosen Zhang
In this work, we focus on the problem of load forecasting.
1 code implementation • 11 Oct 2021 • Yize Chen, Daniel Arnold, Yuanyuan Shi, Sean Peisert
Case studies performed on both voltage regulation and topology control tasks demonstrated the potential vulnerabilities of the standard reinforcement learning algorithms, and possible measures of machine learning robustness and security are discussed for power systems operation tasks.
1 code implementation • 30 Dec 2022 • Chengyang Gu, Hui Xiong, Yize Chen
Solving real-world optimal control problems are challenging tasks, as the complex, high-dimensional system dynamics are usually unrevealed to the decision maker.
Model-based Reinforcement Learning Reinforcement Learning (RL)
1 code implementation • 7 Nov 2023 • Yize Chen, Deepjyoti Deka, Yuanyuan Shi
Each generator can have distinct carbon emission rates.
1 code implementation • 30 Nov 2021 • Yize Chen, Baosen Zhang
Recent proliferation in electric vehicles (EVs) are posing profound impacts over the operation of electrical grids.
1 code implementation • 14 Apr 2022 • Ruohong Liu, Yize Chen
We consider the problem of learning the energy disaggregation signals for residential load data.
1 code implementation • 21 Mar 2024 • Shan Jia, Reilin Lyu, Kangran Zhao, Yize Chen, Zhiyuan Yan, Yan Ju, Chuanbo Hu, Xin Li, Baoyuan Wu, Siwei Lyu
DeepFakes, which refer to AI-generated media content, have become an increasing concern due to their use as a means for disinformation.
1 code implementation • 12 Dec 2023 • Chenghao Huang, Siyang Li, Ruohong Liu, Hao Wang, Yize Chen
Foundation models, such as Large Language Models (LLMs), can respond to a wide range of format-free queries without any task-specific data collection or model training, creating various research and application opportunities for the modeling and operation of large-scale power systems.
1 code implementation • 26 Sep 2022 • Kai-Wen Cheng, Yuexin Bian, Yuanyuan Shi, Yize Chen
This paper examines the problem of optimizing the charging pattern of electric vehicles (EV) by taking real-time electricity grid carbon intensity into consideration.
1 code implementation • 18 Aug 2023 • Siyang Li, Hui Xiong, Yize Chen
Recent proliferation of electric vehicle (EV) charging events has brought prominent stress over power grid operation.
1 code implementation • 21 Feb 2024 • Siyang Li, Hui Xiong, Yize Chen
Accordingly, we devise a novel Diffusion model termed DiffPLF for Probabilistic Load Forecasting of EV charging, which can explicitly approximate the predictive load distribution conditioned on historical data and related covariates.
2 code implementations • 30 Jul 2017 • Yize Chen, Yishen Wang, Daniel Kirschen, Baosen Zhang
We demonstrate that the proposed method is able to generate realistic wind and photovoltaic power profiles with full diversity of behaviors.
1 code implementation • 27 Nov 2022 • Chi Zhang, Yuanyuan Shi, Yize Chen
Recent advancements in reinforcement learning algorithms have opened doors for researchers to operate and optimize building energy management systems autonomously.