Yunfei Mu

Yunfei Mu

Tianjin University

H-index: 39

Asia-China

About Yunfei Mu

Yunfei Mu, With an exceptional h-index of 39 and a recent h-index of 38 (since 2020), a distinguished researcher at Tianjin University, specializes in the field of Power system stability and control, New energy application, Electric vehicle.

His recent articles reflect a diverse array of research interests and contributions to the field:

Online lithium-ion battery intelligent perception for thermal fault detection and localization

Optimal pricing of integrated community energy system for building prosumers with P2P multi-energy trading

The Static Stability Region of an Integrated Electricity-Gas System Considering Voltage and Gas Pressure

Two-stage affine assessment method for flexible ramping capacity: An inverter heat pump virtual power plant case

A simplified control parameter optimisation method of the hybrid modular multilevel converter in the medium‐voltage DC distribution network for improved stability under a weak …

DPGS: Data-driven photovoltaic grid-connected system exploiting deep learning and two-stage single-phase inverter

CWGAN-GP with residual network model for lithium-ion battery thermal image data expansion with quantitative metrics

A real time peer-to-peer energy trading for prosumers utilizing time-varying building virtual energy storage

Yunfei Mu Information

University

Tianjin University

Position

School of Electrical Engineering&Automation

Citations(all)

6255

Citations(since 2020)

5223

Cited By

2714

hIndex(all)

39

hIndex(since 2020)

38

i10Index(all)

94

i10Index(since 2020)

84

Email

University Profile Page

Tianjin University

Yunfei Mu Skills & Research Interests

Power system stability and control

New energy application

Electric vehicle

Top articles of Yunfei Mu

Online lithium-ion battery intelligent perception for thermal fault detection and localization

Authors

Luyu Tian,Chaoyu Dong,Yunfei Mu,Xiaodan Yu,Hongjie Jia

Journal

Heliyon

Published Date

2024/2/29

—Equipping lithium-ion batteries with a reasonable thermal fault diagnosis can avoid thermal runaway and ensure the safe and reliable operation of the batteries. This research built a lithium-ion battery thermal fault diagnosis model that optimized the original mask region-based convolutional neural network based on the battery dataset in both parameters and structure. The model processes the thermal images of the battery surface, identifies problematic batteries, and locates the problematic regions. A backbone network is used to process the battery thermal images and extract feature information. Through the RPN network, the thermal feature is classified and regressed, and the Mask branch is used to ultimately determine the faulty battery's location. Additionally, we have optimized the original mask region-based convolutional neural network based on the battery dataset in both parameters and structure. The …

Optimal pricing of integrated community energy system for building prosumers with P2P multi-energy trading

Authors

Hongjie Jia,Xiaoyu Wang,Xiaolong Jin,Lin Cheng,Yunfei Mu,Xiaodan Yu,Wei Wei

Journal

Applied Energy

Published Date

2024/7/1

Buildings are typically integrated with multiple distributed energy resources (DERs), enabling them to act as building prosumers engaged in both energy production and consumption. Peer-to-peer (P2P) energy trading among building prosumers is crucial to improve their benefits. However, further exploration is required to balance the benefits between building prosumers and the system operator (e.g., the integrated community energy system (ICES) operator) since they are different entities. In this context, this paper proposes a comprehensive network charge and energy sale pricing scheme for the ICES operator on heterogeneous building prosumers with P2P multi-energy trading. The interaction between the ICES operator and building prosumers is modelled as a bi-level optimization problem that belongs to the hierarchical structure, while considering the heterogeneity of thermal insulation performance of …

The Static Stability Region of an Integrated Electricity-Gas System Considering Voltage and Gas Pressure

Authors

Yunfei Mu,Zhibin Liu,Xiangwei Guo,Hongjie Jia,Kai Hou,Xiaodan Yu,Bofeng Luo,Hairun Li

Journal

Engineering

Published Date

2024/2/10

In an integrated electricity-gas system (IEGS), load fluctuations affect not only the voltage in the power system but also the gas pressure in the natural gas system. The static voltage stability region (SVSR) method is a tool for analyzing the overall static voltage stability in a power system. However, in an IEGS, the SVSR boundary may be overly optimistic because the gas pressure may collapse before the voltage collapses. Thus, the SVSR method cannot be directly applied to an IEGS. In this paper, the concept of the SVSR is extended to the IEGS-static stability region (IEGS-SSR) while considering voltage and gas pressure. First, criteria for static gas pressure stability in a natural gas system are proposed, based on the static voltage stability criteria in a power system. Then, the IEGS-SSR is defined as a set of active power injections that satisfies multi-energy flow (MEF) equations and static voltage and gas pressure …

Two-stage affine assessment method for flexible ramping capacity: An inverter heat pump virtual power plant case

Authors

Jiarui Zhang,Yunfei Mu,Zhijun Wu,Hongjie Jia,Xiaolong Jin,Yan Qi

Journal

Applied Energy

Published Date

2024/7/1

The increasing penetration of renewable energy generation brings about variability and randomness, which poses challenges to the power systems due to a potential shortage of flexibility resources. Inverter heat pumps (IHPs) can be utilized to address this issue by providing flexible ramping capacity (FRC). However, unlike conventional generation that offers a fixed FRC, the FRC of individual IHPs and their aggregation are influenced by their operational constraints and the indoor temperature thresholds set by buildings. These thresholds, in turn, are affected by uncertainties in ambient temperature and solar irradiation. For the individual IHP, an IHP-FRC assessment model is established. This individual IHP-FRC assessment model is based on the building thermal dynamic model and user comfort model, incorporating uncertainties in ambient temperature and solar irradiation through affine representations. For the …

A simplified control parameter optimisation method of the hybrid modular multilevel converter in the medium‐voltage DC distribution network for improved stability under a weak …

Authors

Jin Xu,Qian Xiao,Hongjie Jia,Yunfei Mu,Yu Jin,Wenbiao Lu,Shiqian Ma

Journal

IET Energy Systems Integration

Published Date

2024

To improve the stability of the hybrid modular multilevel converter (MMC), a simplified dominant mode‐based control parameter optimisation method of the hybrid MMC system is proposed. Firstly, in the medium‐voltage DC distribution network, the small‐signal model of the hybrid MMC is established. Secondly, the influence of a weak AC system on stability is analysed through eigenvalue analysis. Finally, a simplified objective function is designed for eigenvalues of the dominant mode by considering only real parts, and improved small‐signal stability can be achieved by control parameters optimisation. The proposed method optimises all control parameters at the same time, which further reduces the number of algorithm iterations. Simulation results show that by the proposed control parameter optimisation method, the hybrid MMC has better transient performance and reduced disturbance under SCR variation …

DPGS: Data-driven photovoltaic grid-connected system exploiting deep learning and two-stage single-phase inverter

Authors

Luyu Tian,Chaoyu Dong,Yunfei Mu,Hongjie Jia

Journal

Energy Reports

Published Date

2024/6/1

The increasing demand for clean energy to address the looming energy crisis has led to the widespread use of photovoltaic grid-connected technology, particularly in microgrids. To fully harness solar energy, this study proposes a data-driven strategy for photovoltaic maximum power point tracking with adaptive adjustment to environmental dynamics. Exploiting deep learning and incremental adjustment, our data-driven photovoltaic-grid systems (DPGS) upgrade the traditional perturbation and observation (P&O) MPPT to a dynamic evolutionary scheme. DPGS gathers the photovoltaic panel's output voltage and current, calculates the current power, and then outputs the appropriate reference voltage based on the power difference. The photovoltaic voltage is then adjusted using a data-driven strategy. In this study, a double-hidden layer deep learning network is utilized to output the prediction control signal of the …

CWGAN-GP with residual network model for lithium-ion battery thermal image data expansion with quantitative metrics

Authors

Fengshuo Hu,Chaoyu Dong,Luyu Tian,Yunfei Mu,Xiaodan Yu,Hongjie Jia

Journal

Energy and AI

Published Date

2024/5/1

Lithium batteries find extensive applications in energy storage. Temperature is a crucial indicator for assessing the state of lithium-ion batteries, and numerous experiments require thermal images of lithium-ion batteries for research purposes. However, acquiring thermal imaging samples of lithium-ion battery faults is challenging due to factors such as high experimental costs and associated risks. To address this, our study proposes the utilization of a Conditional Wasserstein Generative Adversarial Network with Gradient Penalty and Residual Network (CWGAN-GP with Residual Network) to augment the dataset of thermal images depicting lithium-ion battery faults. We employ various evaluation metrics to quantitatively analyze and compare the generated thermal images of lithium-ion batteries. Subsequently, the expanded dataset, comprising four types of thermal images depicting lithium-ion battery faults, is input …

A real time peer-to-peer energy trading for prosumers utilizing time-varying building virtual energy storage

Authors

Xiaoyu Wang,Hongjie Jia,Zibo Wang,Xiaolong Jin,Youjun Deng,Yunfei Mu,Xiaodan Yu

Journal

International Journal of Electrical Power & Energy Systems

Published Date

2024/1/1

With the increasing penetration of distributed energy resources (DER) in the electric power system, Peer-to-Peer (P2P) energy trading has become a promising paradigm for future electric power systems. Building thermal load, which is an important demand side resource, should be considered carefully in the design of a P2P trading method. In this paper, we investigate the application of building thermal energy storage capability in P2P energy trading. We aggregate and model building thermal loads as a virtual energy storage and derive a time-varying virtual energy storage system (T-VESS) model to quantify the flexibility of a building. Key parameters of T-VESS, including charging/discharging rate, energy capacity, and state of charge (SOC), are analyzed so that T-VESS can be embedded in the building prosumer model to participate effectively in electricity-oriented P2P energy trading. We propose a real time …

Bi-level optimal operations for grid operator and low-carbon building prosumers with peer-to-peer energy sharing

Authors

Xiaoyu Wang,Hongjie Jia,Xiaolong Jin,Yunfei Mu,Wei Wei,Xiaodan Yu,Shuo Liang

Journal

Applied Energy

Published Date

2024/4/1

Low-carbon buildings (LCBs) are normally equipped with distributed energy resources (DERs) such as photovoltaic (PV) panels and batteries, thereby creating LCB prosumers that both produce and consume energy. Peer-to-peer (P2P) energy sharing among LCB prosumers could bring higher economic benefits for themselves, and facilitate better local power balance for the power grid. To fully harness the benefits of P2P energy sharing for both LCB prosumers and the power grid, a bi-level optimization method for LCB prosumers and the power grid operator is proposed in this paper. The grid operator at the upper level imposes the optimal time-varying network charge to LCB prosumers at the lower level to maximize its profit. And LCB prosumers with the objective of minimizing their costs adjust the schedules including P2P energy sharing and their heating loads to respond to the grid operator's optimal network …

Online Evolutionary Maximum Power Point Tracking for Photovoltaic Grid-connected System

Authors

Luyu Tian,Chaoyu Dong,Bingyu Xiong,Xiangke Li,Yunfei Mu,Hongjie Jia

Published Date

2023/5/12

The utilization of clean energy is increasing because of energy shortage. Meanwhile, the advancement of photovoltaic grid-connected technology has emerged as one widespread approach both domestically and internationally as a crucial component of microgrids. Thus, this study proposes an online evolutionary strategy for photovoltaic maximum power point tracking to fully utilize the solar energy in grid-connected photovoltaic and realize adaptive adjustment of maximum power point tracking control facing environmental dynamics. In this study, the conventional regulation is upgraded into an online evolutionary approach, which deploys incremental adjustment and deep learning. A deep neural network is proposed to continuously modify the weight matrix, which adaptively tunes tracking parameters. In addition, a two-stage single-phase grid-connected photovoltaic inverter is designed with environmental …

Market power modeling and restraint of aggregated prosumers in peer-to-peer energy trading: A game-theoretic approach

Authors

Zibo Wang,Lei Dong,Mengjie Shi,Ji Qiao,Hongjie Jia,Yunfei Mu,Tianjiao Pu

Journal

Applied Energy

Published Date

2023/10/15

The aggregator can be introduced to the community microgrid to facilitate small-scale prosumers participating in peer-to-peer (P2P) energy trading. However, when the aggregator performs price anticipation for profit with its market power, market trading fairness and efficiency of the P2P market may be harmed. To analyze the formation and negative effect of market power, this paper proposes a market power modeling and restraint method of aggregated prosumers with a game-theoretic approach. First, a framework for the P2P energy trading market with the aggregator is established, and the price impact factor is defined and introduced to characterize the impact of the aggregator's trading behavior on the market price. Then, the competition between the aggregator and individual prosumers is modeled as a non-cooperative game, and the impacts of market power on price formation, trading profit, and overall benefit …

Multiphase Converter Voltage Optimization With Minimum Effort Principle

Authors

Qian Xiao,Yu Jin,Josep Pou,Hongjie Jia,Yunfei Mu,Remus Teodorescu,Frede Blaabjerg

Journal

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Published Date

2023/7/1

A large number of control options and steady-state tracking errors are two main challenges for model predictive control in the modular multilevel converter (MMC). To solve these issues, each arm of the three-phase MMC is considered as a whole, and a space-vector-equalized predictive current control scheme is proposed for the three-phase MMC in this article. First, eight equalized space vectors are involved, and only six nonzero vectors are evaluated in each period. As a result, the number of evaluated control options can be significantly reduced. Then, two optimal vectors are selected, and their dwell times are calculated based on the predicted output currents of the MMC. Furthermore, the compensation terms are designed and added to the dwell times so that the steady-state performance can be improved by the proposed scheme. Experimental results show that the proposed scheme provides fast dynamic …

Integrated Energy Microgrids and Low-Carbon Operation Optimization of Coal Mining Areas

Authors

Yunfei Mu,Zhijun Wu,Haochen Guo,Hongjie Jia,Chengshan Wang

Journal

Strategic Study of Chinese Academy of Engineering

Published Date

2023/11/16

Currently, the isolated development of energy in the coal mining areas and the energy supply mode based on coal power generation and grid power supply can no longer satisfy the requirements for implementing clean coal-mining and building a new energy development pattern that is green, low-carbon, and recyclable. Therefore, it is necessary to build integrated energy microgrids in the coal mining areas to enhance the comprehensive utilization of energy and control carbon emissions in these areas. This study explores the demand for and natural advantages of integrated energy microgrids application in the coal mining areas, proposes an integrated energy microgrid framework, and analyzes the development elements of the framework: new energy generation, energy storage, associated energy utilization, multi-energy coupling, and optimal scheduling of energy. A material-energy-carbon hub model is …

Two-stage robust optimization for space heating loads of buildings in integrated community energy systems

Authors

Chenghan Zhou,Hongjie Jia,Xiaolong Jin,Yunfei Mu,Xiaodan Yu,Xiandong Xu,Binghui Li,Weichen Sun

Journal

Applied Energy

Published Date

2023/2/1

A two-stage robust optimization (RO) method for buildings’ space heating loads (SHLs) in an integrated community energy system (ICES) is proposed. At the first stage, a bi-level optimization is deployed to formulate the hierarchical relationship between the ICES operator and consumers in buildings to enable the optimal heating pricing strategy between them. Thermal inertia of SHLs, which is modelled utilizing the Resistor-Capacitor thermal network, is used to provide heating demand response according to the optimal heating sale prices released by the ICES operator. At the second stage, the ICES operator decides the optimal energy purchase schedules from the upper energy systems after the heating sale prices are decided at the first stage. Since the day-ahead energy prices differ from the real-time ones, a RO method is adopted. The original min–max RO problem is converted into its dual problem to …

Electric vehicles acceptance capacity evaluation in distribution network considering photovoltaics access

Authors

Yang Ji,Jian Zhang,Siwei Li,Youjun Deng,Yunfei Mu

Journal

Energy Reports

Published Date

2023/3/1

In the power system with a high proportion of new energy access, the original electric vehicle charging operation mode of the distribution network will change, and the acceptance capacity of electric vehicles also needs to be re-evaluated. In this paper, an evaluation method for the acceptance capacity of electric vehicles is proposed for the distribution network with photovoltaic power generation system installed. Considering the random variation characteristics of the output of the photovoltaic power generation system, seasonal periodicity, and the influence of weather factors, an evaluation model is established. It uses the particle swarm optimization algorithm to calculate the number of electric vehicles that the photovoltaic power generation system can accept, and to analyze the acceptance capacity of the distribution network for electric vehicles. The method utilizes the photovoltaic output to fill the electric vehicle …

WGAN-GP with Residual Network Model for Lithium Battery Thermal Image Data Expansion with Quantitative Metrics

Authors

Fengshuo Hu,Chaoyu Dong,Mingshen Wang,Qian Xiao,Yunfei Mu,Hongjie Jia

Published Date

2023/5/12

Energy storage systems, especially lithium battery energy storage, play a significant role in microgrids. Thermal images of lithium batteries are crucial for the study of lithium batteries since lithium batteries are strongly impacted by temperature. In order to increase the sample of thermal images from lithium batteries, this paper designs the WGAN-GP with ResNet model (Wasserstein generative adversarial network with gradient penalty and residual networks). A complete WGAN-GP with ResNet model is built with the embedding of a generative adversarial network (GAN) structure, introducing gradient penalties, and combining residual networks. The experimental results demonstrate that WGAN-GP with ResNet have a greater improvement in training stability and generated image quality than GAN and Wasserstein GAN by using four evaluation indicators to examine the generated image quality.

Submodule Capacitance Monitoring Approach for the MMC With Asymptotically Converged Error

Authors

Qian Xiao,Huai Wang,Yu Jin,Hongjie Jia,Yunfei Mu,Jiebei Zhu,Remus Teodorescu,Frede Blaabjerg

Journal

IEEE Transactions on Industrial Electronics

Published Date

2023/6/26

To reduce noise interferences and improve the steady-state estimation accuracy of submodule (SM) capacitors, a novel SM capacitance monitoring approach has been proposed for the modular multilevel converter in this article. First, the fundamental frequency (FF) component is analyzed to be dominant of the capacitor voltage squared. Then, based on the energy equation W = Cv 2 /2, half of the FF capacitor voltage squared is selected as the input variable, and the FF capacitor energy calculated by power integral is selected as the feedback component. By proper design of the estimation law, closed-loop capacitance monitoring can be achieved with reduced noise interference. Furthermore, based on the Lyapunov stability criterion, the estimation parameter is designed so that the estimation error asymptotically converges to zero. Compared with the conventional methods, the proposed approach is easy to …

Risk assessment and alleviation of regional integrated energy system considering cross-system failures

Authors

Zeyu Liu,Hang Li,Kai Hou,Xiandong Xu,Hongjie Jia,Lewei Zhu,Yunfei Mu

Journal

Applied Energy

Published Date

2023/11/15

Regional integrated system (RIES) bridges the gaps among different energy systems by various energy conversion equipment. While this integration brings forth numerous benefits, it introduces cross-system failures, where a contingency in one system may affect others. This poses significant challenges when evaluating the consequences of such contingencies. To address this, a risk assessment approach is developed for RIES, considering cross-system failures, as well as fluctuations in renewable generation and multi-energy loads. Event tree analysis (ETA) is adopted to simulate the propagation of failures and identify the affected components. Nine risk indices are proposed to quantify the operational risk of RIES at various levels. Additionally, root cause identification and weak point location are developed to formulate risk alleviation strategies. To validate the proposed method, a RIES with 101 nodes is utilized …

An efficient energy management framework for residential communities based on demand pattern clustering

Authors

Youjun Deng,Fengji Luo,Yongxi Zhang,Yunfei Mu

Journal

Applied Energy

Published Date

2023/10/1

Intelligently managing energy production and consumption on community basis can enhance the demand side energy efficiency. The fact that the number of energy resources (especially controllable appliances) could be large imposes non-trivial computational burden to community-scale energy management. This paper proposes a community energy management framework that coordinately manages the operations of different kinds of energy resources in a community (i.e., photovoltaic solar power sources, battery energy storage systems (BESSs), and controllable appliances from different households) to minimize the community’s energy cost while sufficiently considering the peak-to-average ratio (PAR) of the community’s load and the occupants’ satisfaction. The proposed framework is with a two-stage design: in the day-ahead stage, multiple “virtual appliances” are formed, where each virtual appliance …

Day‐ahead optimal scheduling of building energy microgrids based on time‐varying virtual energy storage

Authors

Yunfei Mu,Yaqing Zhang,Hongjie Jia,Xiaodan Yu,Jiarui Zhang,Xiaolong Jin,Youjun Deng

Journal

IET Renewable Power Generation

Published Date

2023/2

The thermal inertia of a building envelope endows a building with a heat storage capability, introducing scheduling flexibility to a building energy microgrid (BEM). The flexibility is usually modelled as virtual energy storage (VES) and used to optimize the operation of BEMs to reduce electricity costs. However, the VES capacity is impacted by and varies with variations in indoor/outdoor temperature. If only the building envelope's effect on heat transfer is considered, without proper quantification of scheduling flexibility provided by the building envelope, the scheduling scheme (especially VES charging/discharging schemes) will deviate from the actual VES operating conditions, which may affect the thermal comfort of individuals in buildings or bring high electricity costs. In this paper, a time‐varying building VES model (TVES) with three time‐varying parameters (virtual electric capacity (VEC), state of charge (SOC …

See List of Professors in Yunfei Mu University(Tianjin University)

Yunfei Mu FAQs

What is Yunfei Mu's h-index at Tianjin University?

The h-index of Yunfei Mu has been 38 since 2020 and 39 in total.

What are Yunfei Mu's top articles?

The articles with the titles of

Online lithium-ion battery intelligent perception for thermal fault detection and localization

Optimal pricing of integrated community energy system for building prosumers with P2P multi-energy trading

The Static Stability Region of an Integrated Electricity-Gas System Considering Voltage and Gas Pressure

Two-stage affine assessment method for flexible ramping capacity: An inverter heat pump virtual power plant case

A simplified control parameter optimisation method of the hybrid modular multilevel converter in the medium‐voltage DC distribution network for improved stability under a weak …

DPGS: Data-driven photovoltaic grid-connected system exploiting deep learning and two-stage single-phase inverter

CWGAN-GP with residual network model for lithium-ion battery thermal image data expansion with quantitative metrics

A real time peer-to-peer energy trading for prosumers utilizing time-varying building virtual energy storage

...

are the top articles of Yunfei Mu at Tianjin University.

What are Yunfei Mu's research interests?

The research interests of Yunfei Mu are: Power system stability and control, New energy application, Electric vehicle

What is Yunfei Mu's total number of citations?

Yunfei Mu has 6,255 citations in total.

What are the co-authors of Yunfei Mu?

The co-authors of Yunfei Mu are Jianzhong Wu, Hongjie Jia, Janaka Ekanayake, Qian Xiao, Mingshen Wang, xiaohong dong.

    Co-Authors

    H-index: 72
    Jianzhong Wu

    Jianzhong Wu

    Cardiff University

    H-index: 62
    Hongjie Jia

    Hongjie Jia

    Tianjin University

    H-index: 53
    Janaka Ekanayake

    Janaka Ekanayake

    University of Peradeniya

    H-index: 15
    Qian Xiao

    Qian Xiao

    Tianjin University

    H-index: 11
    Mingshen Wang

    Mingshen Wang

    Tianjin University

    H-index: 7
    xiaohong dong

    xiaohong dong

    Tianjin University

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