Search Results for author: Yize Chen

Found 30 papers, 15 papers with code

Learning and Optimization for Price-based Demand Response of Electric Vehicle Charging

no code implementations16 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.

DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging Load

1 code implementation21 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.

Denoising Load Forecasting +2

Interpretable Short-Term Load Forecasting via Multi-Scale Temporal Decomposition

no code implementations18 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.

Load Forecasting

Large Foundation Models for Power Systems

1 code implementation12 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.

Retrieval Scheduling

Long-Term Carbon-Efficient Planning for Geographically Shiftable Resources: A Monte Carlo Tree Search Approach

no code implementations11 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.

Fast Constraint Screening for Multi-Interval Unit Commitment

no code implementations12 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.

DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion Model

1 code implementation18 Aug 2023 Siyang Li, Hui Xiong, Yize Chen

Recent proliferation of electric vehicle (EV) charging events has brought prominent stress over power grid operation.

Denoising Management +1

Dynamic PlenOctree for Adaptive Sampling Refinement in Explicit NeRF

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.

Laxity-Aware Scalable Reinforcement Learning for HVAC Control

no code implementations29 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.

reinforcement-learning Reinforcement Learning (RL)

Learning a Multi-Agent Controller for Shared Energy Storage System

no code implementations16 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.

Multi-agent Reinforcement Learning Scheduling

Pontryagin Optimal Control via Neural Networks

1 code implementation30 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)

Enabling Fast Unit Commitment Constraint Screening via Learning Cost Model

no code implementations1 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.

Targeted Demand Response: Formulation, LMP Implications, and Fast Algorithms

no code implementations27 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.

Benchmarking

BEAR: Physics-Principled Building Environment for Control and Reinforcement Learning

1 code implementation27 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.

energy management Management +3

Carbon-Aware EV Charging

1 code implementation26 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.

Learning Task-Aware Energy Disaggregation: a Federated Approach

1 code implementation14 Apr 2022 Ruohong Liu, Yize Chen

We consider the problem of learning the energy disaggregation signals for residential load data.

Federated Learning Meta-Learning +1

Adam-based Augmented Random Search for Control Policies for Distributed Energy Resource Cyber Attack Mitigation

no code implementations27 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.

SAVER: Safe Learning-Based Controller for Real-Time Voltage Regulation

no code implementations30 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.

State-of-Charge Aware EV Charging

1 code implementation30 Nov 2021 Yize Chen, Baosen Zhang

Recent proliferation in electric vehicles (EVs) are posing profound impacts over the operation of electrical grids.

Scheduling

Improving Robustness of Reinforcement Learning for Power System Control with Adversarial Training

no code implementations18 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.

Decision Making reinforcement-learning +1

Understanding the Safety Requirements for Learning-based Power Systems Operations

1 code implementation11 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.

BIG-bench Machine Learning Decision Making +4

Forecasting Spatio-Temporal Renewable Scenarios: a Deep Generative Approach

no code implementations13 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.

Time Series Analysis

IntelligentCrowd: Mobile Crowdsensing via Multi-Agent Reinforcement Learning

no code implementations20 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

Bayesian Renewables Scenario Generation via Deep Generative Networks

1 code implementation2 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.

Diversity Generative Adversarial Network

An Unsupervised Deep Learning Approach for Scenario Forecasts

1 code implementation7 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

Model-Free Renewable Scenario Generation Using Generative Adversarial Networks

2 code implementations30 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.

Diversity

Blocking Transferability of Adversarial Examples in Black-Box Learning Systems

no code implementations13 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.

Blocking Medical Diagnosis

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