no code implementations • 30 May 2019 • Ye Guo, Ya-Li Li, Shengjin Wang
Generic object detection is one of the most fundamental problems in computer vision, yet it is difficult to provide all the bounding-box-level annotations aiming at large-scale object detection for thousands of categories.
no code implementations • 28 Sep 2020 • Chuanbo Wang, Ye Guo, Wei Chen, Zeyun Yu
With the advance of deep learning, various neural network models have gained great success in image analysis including the recognition of intervertebral discs.
no code implementations • 13 Nov 2019 • Ye Guo, Cong Chen, Lang Tong
Part I investigates dispatch-following incentives of profit-maximizing generators and shows that, under mild conditions, no uniform-pricing scheme for the rolling-window economic dispatch provides dispatch-following incentives that avoid discriminative out-of-the-market uplifts.
no code implementations • 25 Jan 2021 • Cong Chen, Lang Tong, Ye Guo
It is also shown that such settlements give rise to disincentives for generating firms and storage participants to bid truthfully, even when these market participants are rational price-takers in a competitive market.
no code implementations • CVPR 2021 • Zhenyu Wang, YaLi Li, Ye Guo, Lu Fang, Shengjin Wang
In this paper, we delve into semi-supervised object detection where unlabeled images are leveraged to break through the upper bound of fully-supervised object detection models.
no code implementations • 7 May 2021 • Zichao Meng, Ye Guo, Wenjun Tang, Hongbin Sun, Wenqi Huang
A multivariate density forecast model based on deep learning is designed in this paper to forecast the joint cumulative distribution functions (JCDFs) of multiple security margins in power systems.
no code implementations • 16 Jul 2021 • Jiantao Shi, Ye Guo, Lang Tong, Wenchuan Wu, Hongbin Sun
We consider some crucial problems related to the secure and reliable operation of power systems with high renewable penetrations: how much reserve should we procure, how should reserve resources distribute among different locations, and how should we price reserve and charge uncertainty sources.
no code implementations • 24 Sep 2021 • Jiantao Shi, Ye Guo, Lang Tong, Wenchuan Wu, Hongbin Sun
In [1], a single-period co-optimization model of energy and reserve is considered to better illustrate the properties of the co-optimization model and the associated market mechanism.
no code implementations • NeurIPS 2021 • Zhenyu Wang, YaLi Li, Ye Guo, Shengjin Wang
To combat the noisy labeling, we propose noise-resistant semi-supervised learning by quantifying the region uncertainty.
no code implementations • 9 Nov 2021 • Liling Gong, Ye Guo, Hongbin Sun
The optimal operation problem of electric vehicle aggregator (EVA) is considered.
no code implementations • 23 Mar 2022 • Hao liu, Ye Guo, Haitian Liu, Hongbin Sun
We consider the problem of how multiple areas should jointly cover congestion rents of internal and tie-lines in an interconnected power system.
no code implementations • 30 Mar 2022 • Qiong Liu, Ye Guo, Lirong Deng, Haotian Liu, Dongyu Li, Hongbin Sun, Wenqi Huang
Then we design the one-step actor-critic DRL scheme which is a simplified version of recent DRL algorithms, and it avoids the issue of Q value overestimation successfully.
no code implementations • 16 Jun 2022 • Xinyi Yi, Ye Guo, Hongbin Sun
The problem of heat system pricing is considered.
no code implementations • 4 Jul 2022 • Liling Gong, Ye Guo, Hongbin Sun
The optimal operation problem of electric vehicle aggregator (EVA) is considered.
no code implementations • 8 Aug 2022 • Zhihong Huang, Ye Guo, Qiuwei Wu, Li Xiao, Hongbin Sun
With the introduction of the inventory mechanism of REC and CER, the profit of the VPP increases and better trading decisions with multiple markets are made under the requirements of renewable portfolio standard (RPS) and carbon emission (CE) quota requirements.
no code implementations • 17 Aug 2022 • Xinyi Yi, Ye Guo, Hongbin Sun, Qiuwei Wu, Li Xiao
The problem of heat and electricity pricing in combined heat and power systems regarding the time scales of electricity and heat, as well as thermal energy quality, is studied.
no code implementations • 30 Sep 2022 • Yifei Xu, Ye Guo, Wenjun Tang, Hongbin Sun, Shiming Li, Yue Dai
The problem of state estimations for electric distribution system is considered.
no code implementations • 10 Oct 2022 • Qiong Liu, Ye Guo, Lirong Deng, Haotian Liu, Dongyu Li, Hongbin Sun
We investigate that a large action space increases the learning difficulties of DRL and degrades the optimization performance in the process of generating data and training neural networks.
no code implementations • 27 Oct 2022 • Zichao Meng, Ye Guo, Wenjun Tang, Hongbin Sun
This paper proposes a nonparametric multivariate density forecast model based on deep learning.
no code implementations • 2 Apr 2023 • Haitian Liu, Ye Guo, Hao liu
Improving renewable energy resource utilization efficiency is crucial to reducing carbon emissions, and multi-parametric programming has provided a systematic perspective in conducting analysis and optimization toward this goal in smart grid operations.
no code implementations • 8 Aug 2023 • Jiantao Shi, Ye Guo, Wenchuan Wu, Hongbin Sun
In this paper, the intra-day multi-interval rolling-window joint dispatch and pricing of energy and reserve is studied under increasing volatile and uncertain renewable generations.
no code implementations • 15 Aug 2023 • Zichao Meng, Ye Guo, Hongbin Sun
This paper studies an adaptive approach for probabilistic wind power forecasting (WPF) including offline and online learning procedures.
no code implementations • 9 Nov 2023 • Cheng Yang, Rui Xu, Ye Guo, Peixiang Huang, Yiru Chen, Wenkui Ding, Zhongyuan Wang, Hong Zhou
Further, we design two pre-training tasks named object position regression (OPR) and spatial relation classification (SRC) to learn to reconstruct the spatial relation graph respectively.
no code implementations • 23 Nov 2023 • Zhisen Jiang, Ye Guo, Hongbin Sun, Jianxiao Wang
A novel decentralized peer-to-peer-to-grid (P2P2G) trading mechanism considering distribution network integrity is proposed.
no code implementations • 24 Dec 2023 • Wenli Wu, Ye Guo, Jiantao Shi
Potential generator outages and deviations in renewable and load power are modelled through a given number of probability-weighted scenarios.
no code implementations • 26 Feb 2024 • Hanbing Liu, Jingge Wang, Xuan Zhang, Ye Guo, Yang Li
Specifically, we construct a transfer curriculum over the source and intermediate domains based on Wasserstein distance, motivated by theoretical analysis of CDA.