Yang Li

Yang Li
Northeast Electric Power University · School of Electrical Engineering

Doctor of Philosophy
Full Professor at NEEPU, SMIEEE, Clarivate's Highly Cited Researcher, Stanford's Top 2% Scientist

About

224
Publications
22,341
Reads
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4,400
Citations
Introduction
Yang Li, a professor at Northeast Electric Power University in China, specializes in power and renewable energy systems. He holds a Ph.D. in Electrical Engineering, has over 150 peer-reviewed publications, and is an IEEE Senior Member. Dr. Li is recognized on Stanford University's "World's Top 2% Scientists" list (2022-2024) and as a "Highly Cited Chinese Researcher" (2022-2023) by Elsevier.
Additional affiliations
January 2017 - February 2019
Argonne National Laboratory
Position
  • 9700 S. Cass Avenue
Description
  • Postdoc
July 2014 - present
Northeast Electric Power University
Position
  • Jilin
Description
  • Professor
Education
September 2010 - June 2014
North China Electric Power University
Field of study
  • Electrical Engineering

Publications

Publications (224)
Article
Full-text available
A community integrated energy system (CIES) with an electric vehicle charging station (EVCS) provides a new way for tackling growing concerns of energy efficiency and environmental pollution, it is a critical task to coordinate flexible demand response and multiple renewable uncertainties. To this end, a novel bi-level optimal dispatching model for...
Article
Full-text available
Scenario generation is a fundamental and crucial tool for decision-making in power systems with high-penetration renewables. Based on big historical data, a novel federated deep generative learning framework, called Fed-LSGAN, is proposed by integrating federated learning and least square generative adversarial networks (LSGANs) for renewable scena...
Preprint
Full-text available
As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one of the top-priority cyber-related issues and has received increasing attention in recent years. However, so far little attention has been paid to privacy preservation is...
Preprint
Full-text available
A community integrated energy system (CIES) is an important carrier of the energy internet and smart city in geographical and functional terms. Its emergence provides a new solution to the problems of energy utilization and environmental pollution. To coordinate the integrated demand response and uncertainty of renewable energy generation (RGs), a...
Article
Full-text available
Most existing data-driven power system short-term voltage stability assessment (STVSA) approaches presume class-balanced input data. However, in practical applications, the occurrence of short-term voltage instability following a disturbance is minimal, leading to a significant class imbalance problem and a consequent decline in classifier performa...
Article
This paper summarizes the technical activities of a three-year-long IEEE Task Force (TF) on State Estimation (SE) for Integrated Energy Systems (IES). It presents the formal definition and characteristics of IES, along with the comprehensive discussion on Electric Power Systems (EPS) model, and static and dynamic models associated with heating and...
Preprint
This paper introduces a novel approach for tracking the dynamic trajectories of integrated natural gas and power systems, leveraging a Kalman filter-based structure. To predict the states of the system, the Holt's exponential smoothing techniques and nonlinear dynamic equations of gas pipelines are applied to establish the power and gas system equa...
Preprint
To coordinate the interests of operator and users in a microgrid under complex and changeable operating conditions, this paper proposes a microgrid scheduling model considering the thermal flexibility of thermostatically controlled loads and demand response by leveraging physical informed-inspired deep reinforcement learning (DRL) based bi-level pr...
Article
Privacy of user is becoming increasingly significant in constructing efficient multiagent energy management systems for multimicrogrid (MMG). As an emerging privacy-protection method, federated learning (FL) has been used to prevent data breaches in the MMG-related field. However, with the ever-growing participants, the underlying communication bur...
Article
Full-text available
To achieve the sustainable development of the society, renewable energy dominated power systems are gradually formed. However, the uncertainty of renewable power poses challenges for power system operations, such as balancing the load and generation in day‐ahead unit commitment problems. To address this issue, an enhanced disjointed layered ambigui...
Article
Full-text available
The emergence of novel the dummy data injection attack (DDIA) poses a severe threat to the secure and stable operation of power systems. These attacks are particularly perilous due to the minimal Euclidean spatial separation between the injected malicious data and legitimate data, rendering their precise detection challenging using conventional dis...
Article
Full-text available
The accurate modeling of uncertain variables, such as wind power and load uncertainty, is an essential foundation for the planning operation and scheduling decisions in power systems. Currently, Gaussian mixture model (GMM) and Dirichlet process mixture model (DPMM) are the primary techniques used to characterize uncertainties in power systems, whi...
Chapter
Currently, human development is significantly constrained by energy and environmental crises. Renewable energy (RE) is considered as the solution for replacing conventional energy, because it is more environmentally friendly (Yang et al. in Proceedings of the 2017 IEEE 56th Annual Conference on Decision and Control (CDC), pp 6334–6339, 2017; Dou et...
Chapter
Environmental pollution and the depletion of traditional fossil fuels are pressing concerns. As a response, the international community is pursuing the development of renewable generation (RG) and improvements in energy efficiency (Wang et al. in Nat Commun 11:1–11, 2020;Ding et al. in IEEE Trans Ind Appl 55:2198–2207, 2019;). The integration of el...
Chapter
Data center microgrids (DCMGs) have been recently established to address the above challenging issues of electricity cost and environmental impact. Therein, various work have contributed to reduce the cost of DCs.
Chapter
To replace the conventional thermal power on the supply side, the connection of high-capacity renewable energy, such as wind power (WP) is considered to be one of the effective methods.
Chapter
With the development of information technology, such as big data, internet of things, and cloud computing, the demands for data storage, computing, and processing are growing explosively.
Chapter
Flexible load control refers to the ability to manage and adjust the consumption of electrical loads in response to changing energy supply and demand conditions.
Chapter
In recent years, electric vehicles (EVs) and their charging stations have been extensively utilized to promote clean, efficient, and sustainable energy development (Liu et al. in IEEE Trans Ind Electr 62:2560–2570, 2015; Ding et al. in IEEE Trans Ind Appl 54:5590–5598, 2018; Chaudhari et al. in IEEE Trans Ind Inform 14:106–116, 2018). The Internati...
Chapter
Recently, the depletion of fossil fuels and escalating environmental pollution have emerged as primary challenges confronting human civilization. The advent and progression of renewable generations (RGs) present a viable solution to such issues (Potrč et al. in Renew Sustain Energy Rev 146:111186, 2021). A prominent illustration of this solution an...
Chapter
Renewable energy (RE) has been deployed significantly in recent years. Obviously, it is a suitable substitute of traditional thermal generators to achieve sustainable development of the world (Zhao et al. in IEEE Trans Ind Inform 16(5):3460–3469, 2020; Kumar et al. in IEEE Trans Ind Inform 15(5):2947–2957, 2019; Rehmani et al. in IEEE Trans Ind Inf...
Chapter
In the present day, the sustainable development of modern society is threatened by the energy crisis and global warming. Efficient use of renewable generations (RGs) such as wind turbines (WT) and photovoltaic (PV), and rapid advancements in electric vehicles (EVs) present an opportunity to address these issues (Lv et al. in IEEE Trans Industr Inf...
Article
The integration of renewable energy (RE) into the active distribution network (ADN) leads to frequent changes in its operational state, requiring the ADN to be more proactive in ensuring system safety and stability. Active distribution network reconfiguration (ADNR) is a method that aims to balance loads and optimize the system's topology. It has b...
Article
The rapid development of renewable energy sources (RESs) has led to their increased integration into microgrids (MGs), emphasizing the need for safe and efficient energy management in MG operations. We investigate the methods of MG energy management, primarily categorized into model-based and model-free approaches. Due to a lack of incremental know...
Article
Robust optimization (RO) has been widely used in the hydrogen-data-center microgrid (H $_2$ -DCMG) optimal operations. However, the operation results based on RO are too conservative. Statistical feasibility can be introduced into RO to reduce conservatism. Therefore, statistical feasibility-based RO is adopted in the H $_2$ -DCMG operations opti...
Article
To coordinate the interests of operator and users in a microgrid under complex and changeable operating conditions, this paper proposes a microgrid scheduling model considering the thermal flexibility of thermostatically controlled loads and demand response by leveraging physical informed-inspired deep reinforcement learning (DRL) based bi-level pr...
Article
Full-text available
The restoration control of the modern alternating current-direct current (AC-DC) hybrid power grid after a major blackout is difficult and complex. Taking into account the interaction between the line-commutated converter high-voltage direct current (LCC-HVDC) and the AC power grid, this paper proposes a novel optimization method of restoration pat...
Article
Full-text available
Background The contemporary landscape of power and energy systems (P&ESs) is experiencing a significant transformation, marked by the integration of distributed energy resources (DERs) like solar photovoltaics, wind turbines, energy storage systems, and electric vehicles. Although these DERs bring forth myriad benefits, they also introduce challeng...
Article
Deep learning has emerged as an effective solution for addressing the challenges of short-term voltage stability assessment (STVSA) in power systems. However, existing deep learning-based STVSA approaches face limitations in adapting to topological changes, sample labeling, and handling small datasets. To overcome these challenges, this paper propo...
Article
Full-text available
Aiming at how to reduce the frequency modulation loss of thermal power units, improve the frequency modulation performance of the system and reduce the life cycle cost of energy storage, a dual-level optimal configuration model of hybrid energy storage assisted thermal power units participating in Automatic Generation Control (AGC) is proposed. The...
Preprint
Deep learning has emerged as an effective solution for addressing the challenges of short-term voltage stability assessment (STVSA) in power systems. However, existing deep learning-based STVSA approaches face limitations in adapting to topological changes, sample labeling, and handling small datasets. To overcome these challenges, this paper propo...
Article
Full-text available
A three-phase isolated AC-DC-DC power supply is widely used in the industrial field due to its attractive features such as high-power density, modularity for easy expansion and electrical isolation. In high-power application scenarios, it can be realized by multiple AC-DC-DC modules with Input-Parallel Output-Parallel (IPOP) mode. However, it has t...
Article
Full-text available
To achieve the net zero emission of greenhouse gases, renewable energy (RE) has been highly penetrated into the power system. However, the high absorption of RE may violate operational constraints of the power system and impact its secure and economic operation. In contrast, if some of the penetrated RE is curtailed, the above issue would be addres...
Preprint
Achieving the economical and stable operation of Multi-microgrids (MMG) systems is vital. However, there are still some challenging problems to be solved. Firstly, from the perspective of stable operation, it is necessary to minimize the energy fluctuation of the main grid. Secondly, the characteristics of energy conversion equipment need to be con...
Preprint
Full-text available
Offshore wind power is an important part of the new power system, due to the complex and changing situation at ocean, its normal operation and maintenance cannot be done without information such as images, therefore, it is especially important to transmit the correct image in the process of information transmission. In this paper, we propose a new...
Article
Full-text available
Achieving the economical and stable operation of Multi-microgrids (MMG) systems is vital. However, there are still some challenging problems to be solved. Firstly, from the perspective of stable operation, it is necessary to minimize the energy fluctuation of the main grid. Secondly, the characteristics of energy conversion equipment need to be con...
Article
Full-text available
The implementation of a multi-microgrid (MMG) system with multiple renewable energy sources enables the facilitation of electricity trading. To tackle the energy management problem of an MMG system, which consists of multiple renewable energy microgrids belonging to different operating entities, this paper proposes an MMG collaborative optimization...
Preprint
Full-text available
The implementation of a multi-microgrid (MMG) system with multiple renewable energy sources enables the facilitation of electricity trading. To tackle the energy management problem of a MMG system, which consists of multiple renewable energy microgrids belonging to different operating entities, this paper proposes a MMG collaborative optimization s...
Article
Full-text available
The utilization of large-scale distributed renewable energy (RE) promotes the development of the multimicrogrid (MMG), which raises the need of developing an effective energy management method to minimize economic costs and keep self energy sufficiency. The multiagent deep reinforcement learning (MADRL) has been widely used for the energy managemen...
Article
Full-text available
With the development of smart grid, the operation and control of power system is realized through power communication network, especially the power production and enterprise management business involve a large amount of sensitive information, and the requirements for data security and real-time transmission are gradually improved. In this paper, a...
Article
Full-text available
In a modern power system with an increasing proportion of renewable energy, wind power prediction is crucial to the arrangement of power grid dispatching plans due to the volatility of wind power. However, traditional centralized forecasting methods raise concerns regarding data privacy-preserving and data islands problem. To handle the data privac...
Book
Full-text available
As the demand for sustainable and efficient energy solutions continues to grow, researchers worldwide are making significant strides in various domains of energy research. Recognising the future leaders of Energy Research is fundamental to safeguarding tomorrow’s driving force in innovation. This Research Topic aims to provide a comprehensive over...
Article
Full-text available
The demand response of data center is considered as an effective flexible method to absorb excessive renewable energy (RE) in the power system, especially for the data center with high-density hydrogen storages. Therefore, this paper proposes a collaborative response framework considering regulations of data workload and hydrogen storage. It is exp...
Article
Industrial demand response (IDR) plays an important role in promoting the utilization of renewable energy (RE) in power systems. However, it will lead to power adjustments on the supply side, which is also a nonnegligible factor in affecting RE utilization. To comprehensively analyze this impact while enhancing RE utilization, this article proposes...
Preprint
The utilization of large-scale distributed renewable energy promotes the development of the multi-microgrid (MMG), which raises the need of developing an effective energy management method to minimize economic costs and keep self energy-sufficiency. The multi-agent deep reinforcement learning (MADRL) has been widely used for the energy management p...
Preprint
Full-text available
Multi-uncertainties from power sources and loads have brought significant challenges to the stable demand supply of various resources at islands. To address these challenges, a comprehensive scheduling framework is proposed by introducing a model-free deep reinforcement learning (DRL) approach based on modeling an island integrated energy system (I...
Preprint
In a modern power system with an increasing proportion of renewable energy, wind power prediction is crucial to the arrangement of power grid dispatching plans due to the volatility of wind power. However, traditional centralized forecasting methods raise concerns regarding data privacy-preserving and data islands problem. To handle the data privac...
Preprint
Full-text available
In recent years, with the development of wind energy, the number and scale of wind farms are developing rapidly. Since offshore wind farm has the advantages of stable wind speed, clean, renewable, non-polluting and no occupation of cultivated land, which has gradually become a new trend of wind power industry all over the world. The operation and m...
Article
Full-text available
The development of miniaturized nuclear power (NP) units and the improvement of the carbon trading market provide a new way to realize the low-carbon operation of integrated energy systems (IES). In this study, NP units and carbon trading mechanisms are introduced into the IES to build a new low-carbon scheduling model. In view of the decrease in s...
Preprint
The development of miniaturized nuclear power (NP) units and the improvement of the carbon trading market provide a new way to realize the low-carbon operation of integrated energy systems (IES). In this study, NP units and carbon trading mechanisms are introduced into the IES to build a new low-carbon scheduling model. In view of the decrease in s...
Preprint
Full-text available
Towards developing effective and efficient brain-computer interface (BCI) systems, precise decoding of brain activity measured by electroencephalogram (EEG), is highly demanded. Traditional works classify EEG signals without considering the topological relationship among electrodes. However, neuroscience research has increasingly emphasized network...
Preprint
Full-text available
In response to the damage to electric power transmission systems caused by typhoon disasters in coastal areas, a planning-targeted resilience assessment framework that considers the impact of multiple factors is established to accurately find the weak links of the transmission system and improve the system resilience. Firstly, this paper constructs...
Article
Full-text available
The operating conditions of the power system have become more complex and changeable. This paper proposes a probabilistic power flow calculation method based on the cumulant method for the voltage sourced converter high voltage direct current (VSC-HVDC) hybrid system containing photovoltaic grid-connected systems. Firstly, the corresponding control...
Preprint
An automatic encoder (AE) extreme learning machine (ELM)-AE-ELM model is proposed to predict the NOx emission concentration based on the combination of mutual information algorithm (MI), AE, and ELM. First, the importance of practical variables is computed by the MI algorithm, and the mechanism is analyzed to determine the variables related to the...
Preprint
Full-text available
With the development of smart grid, the operation and control of power system is realized through power communication network, especially the power production and enterprise management business involve a large amount of sensitive information, and the requirements for data security and real-time transmission are gradually improved. In this paper, a...
Article
Full-text available
An automatic encoder (AE) extreme learning machine (ELM)-AE-ELM model is proposed to predict the NOx emission concentration based on the combination of mutual information algorithm (MI), AE, and ELM. First, the importance of practical variables is computed by the MI algorithm, and the mechanism is analyzed to determine the variables related to the...
Preprint
Full-text available
With the rapid development of the energy internet, the proportion of flexible loads in smart grid is getting much higher than before. It is highly important to model flexible loads based on demand response. Therefore, a new demand response method considering multiple flexible loads is proposed in this paper to character the integrated demand respon...
Preprint
District energy systems can not only reduce energy consumption but also set energy supply dispatching schemes according to demand. In addition to economic cost, energy consumption and pollutant are more worthy of attention when evaluating combined cooling, heating and power (CCHP) models. In this paper, the CCHP model is established with the object...
Article
Full-text available
The knowledge of the users’ electricity consumption pattern is an important coordinating mechanism between the utility company and the electricity consumers in terms of key decision makings. The load decomposition is therefore crucial to reveal the underlying relationship between the load consumption and its characteristics. However, load decomposi...
Article
Full-text available
District energy systems can not only reduce energy consumption but also set energy supply dispatching schemes according to demand. In addition to economic cost, energy consumption and pollutant are more worthy of attention when evaluating combined cooling, heating and power (CCHP) models. In this paper, the CCHP model is established with the object...
Article
Full-text available
With the rapid advancement of the Energy Internet strategy, the number of sensors within the Power Distribution Internet of Things (PD-IoT) has increased dramatically. In this paper, an edge intelligence-based PD-IoT multi-source data processing and fusion method is proposed to solve the problems of confusing storage and insufficient fusion computi...
Article
Full-text available
The electric vehicle (EV) and electric vehicle charging station (EVCS) have been widely deployed with the development of large-scale transportation electrifications. However, since charging behaviors of EVs show large uncertainties, the forecasting of EVCS charging power is non-trivial. This paper tackles this issue by proposing a reinforcement lea...
Preprint
Full-text available
The electric vehicle (EV) and electric vehicle charging station (EVCS) have been widely deployed with the development of large-scale transportation electrifications. However, since charging behaviors of EVs show large uncertainties, the forecasting of EVCS charging power is non-trivial. This paper tackles this issue by proposing a reinforcement lea...
Article
Full-text available
In recent years, with the development of wind energy, the number and scale of wind farms have been developing rapidly. Since offshore wind farms have the advantages of stable wind speed, being clean, renewable, non-polluting, and the non-occupation of cultivated land, they have gradually become a new trend in the wind power industry all over the wo...
Article
Full-text available
In order to improve the penetration of renewable energy resources for distribution networks, a joint planning model of distributed generations (DGs) and energy storage is proposed for an active distribution network by using a bi-level programming approach in this paper. In this model, the upper-level aims to seek the optimal location and capacity o...
Preprint
Full-text available
With the rapid advancement of the Energy Internet strategy, the number of sensors within the Power Distribution Internet of Things (PD-IoT) has increased dramatically. In this paper, an edge intelligence-based PD-IoT multi-source data processing and fusion method is proposed to solve the problems of confusing storage and insufficient fusion computi...
Article
Full-text available
The community integrated energy system (CIES) is an essential energy internet carrier that has recently been the focus of much attention. A scheduling model based on chance-constrained programming is proposed for integrated demand response (IDR)-enabled CIES in uncertain environments to minimize the system operating costs, where an IDR program is u...
Preprint
Full-text available
The knowledge of the users' electricity consumption pattern is an important coordinating mechanism between the utility company and the electricity consumers in terms of key decision makings. The load decomposition is therefore crucial to reveal the underlying relationship between the load consumption and its characteristics. However, load decomposi...
Article
Nonintrusive load monitoring (NILM) is crucial for extracting patterns of electricity consumption of household appliance that can guide users’ behavior in using electricity while their privacy is respected. This study proposes an online method based on the transient behavior of individual appliances as well as system steady-state characteristics to...
Article
Full-text available
In this paper, a novel Gaussian bare-bones bat algorithm (GBBBA) and its modified version named as dynamic exploitation Gaussian bare-bones bat algorithm (DeGBBBA) are proposed for solving optimal reactive power dispatch (ORPD) problem. The optimal reactive power dispatch (ORPD) plays a fundamental role in ensuring stable, secure, reliable as well...