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Jianhui Wang - IEEE Xplore Author Profile

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Author details

Jianhui Wang

Also published under: J. Wang

Publications

336

Citations

30,338

Publications by Year

20082025

Co-Authors:

Farzaneh AbbaspourtorbatiQian AiNatalia AlguacilAbdulraheem H. AlobaidiPayman Arabshahi

Show All Co-Authors (398)

Jianhui Wang

Also published under: J. Wang

Affiliation

Department of Electrical and Computer Engineering

Southern Methodist University

Dallas, TX, USA

Publication Topics

Power System,
Distributed Energy Resources,
Energy Storage Systems,
Neural Network,
Deep Reinforcement Learning,
Load Shedding,
Model Predictive Control,
Deep Learning,
Deep Neural Network,
Linear Problem,
Microgrid,
Mixed Integer Linear Programming

Biography

Jianhui Wang received his B.S. degree in management science and engineering (2001) and a M.S. degree in technical economics and management (2004), both from North China Electric Power University, China, and his Ph.D. in electrical engineering from Illinois Institute of Technology, USA (2007). Presently, he is an assistant computational engineer - Energy Systems with CEEESA at Argonne National Laboratory. His research interests include energy economics and policy, agent-based modeling and simulation, and electric power systems optimization and economics. He is chair of the IEEE PES power system operation methods subcommittee and co-chair of the task force on integration of wind and solar power into power system operations.(Based on document published on 10 October 2011).

Publications

336

Citations

30,338

Publications by Year

20082025

Co-Authors:

Farzaneh Abbaspourtorbati
Qian Ai
Natalia Alguacil
Abdulraheem H. Alobaidi
Payman Arabshahi

Show All Co-Authors (398)

Author's Published Works

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Showing 1-25 of 336 results

Journals (275)

Conferences (56)

Magazines (4)

Early Access Articles (1)

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Jianhui Wang(330)
Chen Chen(36)
Zhaoyu Wang(26)
Hongbin Sun(24)
Xiaonan Lu(23)
Department of Electrical Engineering, Southern Methodist University, Dallas, TX, USA(60)
Argonne National Laboratory, Argonne, IL, USA(53)
Department of Electrical and Computer Engineering, Southern Methodist University, Dallas, TX, USA(43)
Energy Systems Division, Argonne National Laboratory, Argonne, IL, USA(36)
Department of Electrical Engineering, Tsinghua University, Beijing, China(29)
IEEE Transactions on Power Systems(125)
IEEE Transactions on Smart Grid(93)
IEEE Transactions on Sustainable Energy(24)
2019 IEEE Power & Energy Society General Meeting (PESGM)(7)
IEEE Transactions on Industrial Informatics(6)
IEEE(336)
Media(2)
Atlanta, GA, USA(7)
Washington, DC, USA(7)
Montreal, QC, Canada(5)
Calgary, AB, Canada(4)
Portland, OR, USA(4)
Power System(147)
Wind Power(77)
Microgrid(73)
Distribution System(64)
Wind Farm(49)

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Optimal Scheduling for Networked Microgrids Considering Back-to-Back MVDC Systems

Anping Zhou;Jianhui Wang;Mohammad E. Khodayar

IEEE Transactions on Smart Grid

Year: 2025 | Early Access Article |

Networked microgrids (MGs) have emerged as a favored and promising scheme to facilitate the integration of distributed energy resources and enhance the resiliency of power support. To advance the flexible operation of distribution systems, this paper proposes an optimal scheduling model for networked MGs, embedding three innovative medium-voltage direct current (MVDC) technologies with voltage sou...Show More

Optimal Scheduling for Networked Microgrids Considering Back-to-Back MVDC Systems

Anping Zhou;Jianhui Wang;Mohammad E. Khodayar

IEEE Transactions on Smart Grid

Year: 2025 | Early Access Article |

Event-Based Hybrid Bi-Level Energy Management and Control Framework of Networked Microgrid

Tao Wu;Jianhui Wang;Tianqiao Zhao;Anping Zhou;Badrul Chowdhury;Robert Cox

IEEE Transactions on Smart Grid

Year: 2025 | Volume: 16, Issue: 2 | Journal Article |

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Networked microgrids (NMGs) are favorable for enhancing the operating efficiency under normal operations and maintaining energy supply to critical facilities during abnormal conditions in the face of severe outages. This paper proposes an event-based hybrid bi-level energy management and control framework for NMGs. We first propose a hybrid bi-level energy management and control system, incorporat...Show More

Event-Based Hybrid Bi-Level Energy Management and Control Framework of Networked Microgrid

Tao Wu;Jianhui Wang;Tianqiao Zhao;Anping Zhou;Badrul Chowdhury;Robert Cox

IEEE Transactions on Smart Grid

Year: 2025 | Volume: 16, Issue: 2 | Journal Article |

Back-to-Back DC Transmission System Embedded Scheduling With Integrated Hydrogen Injection Modeling

Anping Zhou;Jianhui Wang;Meng Yue

IEEE Transactions on Smart Grid

Year: 2025 | Volume: 16, Issue: 1 | Journal Article |

Cited by: Papers (1)

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As the issue of short-circuit currents becomes increasingly critical in contemporary ever-expanding power grids, back-to-back DC transmission systems (BDTSs) have emerged as a promising scheme to address such a concern. However, the study on the practical and accurate modeling of BDTSs in typical power system decision-making problems remains profoundly limited. To bridge this research gap, we form...Show More

Back-to-Back DC Transmission System Embedded Scheduling With Integrated Hydrogen Injection Modeling

Anping Zhou;Jianhui Wang;Meng Yue

IEEE Transactions on Smart Grid

Year: 2025 | Volume: 16, Issue: 1 | Journal Article |

Evidential Reasoning for Enhanced Node Selection in Power Network Reduction: a Complex Network Perspective

Bin Huang;Jiayong Li;Han Guo;Jianhui Wang

2024 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2024 | Conference Paper |

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An effective node selection criterion (NSC) is paramount for the efficient reduction of networks in power systems. Unlike prior studies that primarily focus on structural attributes, this paper introduces a comprehensive NSC that encompasses both structural and electrical characteristics. This NSC is formulated using the evidential reasoning approach. Within this framework, quasi-one-hot encoding ...Show More

Evidential Reasoning for Enhanced Node Selection in Power Network Reduction: a Complex Network Perspective

Bin Huang;Jiayong Li;Han Guo;Jianhui Wang

2024 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2024 | Conference Paper |

Distributionally Robust Optimal Scheduling With Heterogeneous Uncertainty Information: A Framework for Hydrogen Systems

Anping Zhou;Mohammad E. Khodayar;Jianhui Wang

IEEE Transactions on Sustainable Energy

Year: 2024 | Volume: 15, Issue: 3 | Journal Article |

Cited by: Papers (1)

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Distributionally robust optimization (DRO) has emerged as a favored methodology for addressing the uncertainties stemming from renewable energy sources. However, existing DRO frameworks primarily focus on single types of uncertainty characteristics, such as moments. Exploring novel ambiguity sets that encompass heterogeneous uncertainty information to mitigate decision conservatism is thus an esse...Show More

Distributionally Robust Optimal Scheduling With Heterogeneous Uncertainty Information: A Framework for Hydrogen Systems

Anping Zhou;Mohammad E. Khodayar;Jianhui Wang

IEEE Transactions on Sustainable Energy

Year: 2024 | Volume: 15, Issue: 3 | Journal Article |

Distributionally Robust Multistage Dispatch With Discrete Recourse of Energy Storage Systems

Xiaodong Zheng;Mohammad E. Khodayar;Jianhui Wang;Meng Yue;Anping Zhou

IEEE Transactions on Power Systems

Year: 2024 | Volume: 39, Issue: 6 | Journal Article |

Cited by: Papers (27)

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Energy storage systems (ESS) are indispensable building blocks of power systems with a high share of variable renewable energy. As energy-limited resources, ESS should be carefully modeled in uncertainty-aware multistage dispatch. On the modeling side, we develop a two-stage model for ESS that respects the nonanticipativity of multistage dispatch, and implement it into a distributionally robust mo...Show More

Distributionally Robust Multistage Dispatch With Discrete Recourse of Energy Storage Systems

Xiaodong Zheng;Mohammad E. Khodayar;Jianhui Wang;Meng Yue;Anping Zhou

IEEE Transactions on Power Systems

Year: 2024 | Volume: 39, Issue: 6 | Journal Article |

Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control

Ying Zhang;Meng Yue;Jianhui Wang;Shinjae Yoo

IEEE Transactions on Neural Networks and Learning Systems

Year: 2024 | Volume: 35, Issue: 3 | Journal Article |

Cited by: Papers (9)

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Grid emergency voltage control (GEVC) is paramount in electric power systems to improve voltage stability and prevent cascading outages and blackouts in case of contingencies. While most deep reinforcement learning (DRL)-based paradigms perform single agents in a static environment, real-world agents for GEVC are expected to cooperate in a dynamically shifting grid. Moreover, due to high uncertain...Show More

Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control

Ying Zhang;Meng Yue;Jianhui Wang;Shinjae Yoo

IEEE Transactions on Neural Networks and Learning Systems

Year: 2024 | Volume: 35, Issue: 3 | Journal Article |

A Fast Quantum Algorithm for Searching the Quasi-Optimal Solutions of Unit Commitment

Xiaodong Zheng;Jianhui Wang;Meng Yue

IEEE Transactions on Power Systems

Year: 2024 | Volume: 39, Issue: 2 | Journal Article |

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The electric power industry faces tough optimization problems that are challenging for classical computers, e.g., the unit commitment (UC). Quantum computing has the potential to provide a speedup for combinatorial optimization problems utilizing ad hoc algorithms like Grover's search algorithm. The quantum oracle is indispensable for Grover's search, yet it is difficult to realize. In this letter...Show More

A Fast Quantum Algorithm for Searching the Quasi-Optimal Solutions of Unit Commitment

Xiaodong Zheng;Jianhui Wang;Meng Yue

IEEE Transactions on Power Systems

Year: 2024 | Volume: 39, Issue: 2 | Journal Article |

Bi-Level Adaptive Storage Expansion Strategy for Microgrids Using Deep Reinforcement Learning

Bin Huang;Tianqiao Zhao;Meng Yue;Jianhui Wang

IEEE Transactions on Smart Grid

Year: 2024 | Volume: 15, Issue: 2 | Journal Article |

Cited by: Papers (7)

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Battery energy storage (BES) is a versatile resource for the secure and economic operation of microgrids (MGs). Prevailing stochastic optimization-based approaches for BES expansion planning for MGs are computationally complicated. This work proposes a data-driven bi-level multi-period BES expansion planning framework to determine the siting, sizing, and timing of BES installations. The proposed p...Show More

Bi-Level Adaptive Storage Expansion Strategy for Microgrids Using Deep Reinforcement Learning

Bin Huang;Tianqiao Zhao;Meng Yue;Jianhui Wang

IEEE Transactions on Smart Grid

Year: 2024 | Volume: 15, Issue: 2 | Journal Article |

Transient Stability-Constrained Unit Commitment Using Input Convex Neural Network

Tao Wu;Jianhui Wang

IEEE Transactions on Neural Networks and Learning Systems

Year: 2024 | Volume: 35, Issue: 11 | Journal Article |

Cited by: Papers (3)

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This article proposes a transient stability-constrained unit commitment (TSC-UC) model using input convex neural networks (ICNNs). An ICNN is trained to learn the transient function that maps prefault operation conditions (e.g., generator power output) to the transient stability index (TSI), which can be further utilized to identify the transient status (e.g., stable or unstable). Transient stabil...Show More

Transient Stability-Constrained Unit Commitment Using Input Convex Neural Network

Tao Wu;Jianhui Wang

IEEE Transactions on Neural Networks and Learning Systems

Year: 2024 | Volume: 35, Issue: 11 | Journal Article |

Free-Form Dynamic Load Model Synthesis With Symbolic Regression Based on Sparse Dictionary Learning

You Lin;Jianhui Wang;Meng Yue

IEEE Transactions on Power Systems

Year: 2024 | Volume: 39, Issue: 2 | Journal Article |

Cited by: Papers (1)

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With the increasing integration of distributed energy resources, significant efforts have been made to develop more accurate load models to mimic the dynamic response of power system load. Despite the prevalence of high-resolution measurement equipment and artificial intelligence algorithms, the increasing complexity in existing load models has restricted their accuracy, effectiveness, and capabil...Show More

Free-Form Dynamic Load Model Synthesis With Symbolic Regression Based on Sparse Dictionary Learning

You Lin;Jianhui Wang;Meng Yue

IEEE Transactions on Power Systems

Year: 2024 | Volume: 39, Issue: 2 | Journal Article |

Adaptive Static Equivalences for Active Distribution Networks With Massive Renewable Energy Integration: A Distributed Deep Reinforcement Learning Approach

Bin Huang;Jianhui Wang

IEEE Transactions on Network Science and Engineering

Year: 2024 | Volume: 11, Issue: 6 | Journal Article |

Cited by: Papers (5)

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Active distribution networks (ADNs) with 100% renewable energy sources (RESs) penetration are essential in the net-zeros emission power sector. As an efficient analysis tool, the equivalent model for ADNs (EMADNs) can be leveraged to expedite the lengthy analysis and preserve data privacy. Nevertheless, volatile RESs, along with their active management techniques, e.g., voltage regulation schemes ...Show More

Adaptive Static Equivalences for Active Distribution Networks With Massive Renewable Energy Integration: A Distributed Deep Reinforcement Learning Approach

Bin Huang;Jianhui Wang

IEEE Transactions on Network Science and Engineering

Year: 2024 | Volume: 11, Issue: 6 | Journal Article |

Deep-Learning-Based Koopman Modeling for Online Control Synthesis of Nonlinear Power System Transient Dynamics

Tianqiao Zhao;Meng Yue;Jianhui Wang

IEEE Transactions on Industrial Informatics

Year: 2023 | Volume: 19, Issue: 10 | Journal Article |

Cited by: Papers (8)

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Power system stability and control have become more challenging due to the increasing uncertainty associated with renewable generation. The performance of conventional control is highly driven by the physics-based offline-developed dynamic models that can deviate from the actual system characteristics under different operating conditions and/or configurations. Data-driven approaches based on onlin...Show More

Deep-Learning-Based Koopman Modeling for Online Control Synthesis of Nonlinear Power System Transient Dynamics

Tianqiao Zhao;Meng Yue;Jianhui Wang

IEEE Transactions on Industrial Informatics

Year: 2023 | Volume: 19, Issue: 10 | Journal Article |

A Barrier-Certificated Reinforcement Learning Approach for Enhancing Power System Transient Stability

Tianqiao Zhao;Jianhui Wang;Meng Yue

IEEE Transactions on Power Systems

Year: 2023 | Volume: 38, Issue: 6 | Journal Article |

Cited by: Papers (9)

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Increasing integration of renewable resources brings more flexibility and poses new challenges to modern power systems, leading to highly nonlinear and complex dynamics. This paper aims to provide a general solution framework to traditional control problems, such as frequency control and voltage control, which attempt to maintain the stability of either synchronous generators-governed or inverter-...Show More

A Barrier-Certificated Reinforcement Learning Approach for Enhancing Power System Transient Stability

Tianqiao Zhao;Jianhui Wang;Meng Yue

IEEE Transactions on Power Systems

Year: 2023 | Volume: 38, Issue: 6 | Journal Article |

Robust Power System Stability Assessment Against Adversarial Machine Learning-Based Cyberattacks via Online Purification

Tianqiao Zhao;Meng Yue;Jianhui Wang

IEEE Transactions on Power Systems

Year: 2023 | Volume: 38, Issue: 6 | Journal Article |

Cited by: Papers (10)

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The increasing complexity associated with renewable generation brings more challenges to power system stability assessment (SA). Data-driven approaches based on machine learning (ML) techniques for stability assessment have received significant research interest and shown their promising performance. However, ML-based models are recognized to be vulnerable to adversarial disturbances, where a slig...Show More

Robust Power System Stability Assessment Against Adversarial Machine Learning-Based Cyberattacks via Online Purification

Tianqiao Zhao;Meng Yue;Jianhui Wang

IEEE Transactions on Power Systems

Year: 2023 | Volume: 38, Issue: 6 | Journal Article |

Quantitative Metrics for Grid Resilience Evaluation and Optimization

Yiyun Yao;Weijia Liu;Rishabh Jain;Badrul Chowdhury;Jianhui Wang;Robert Cox

IEEE Transactions on Sustainable Energy

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Cited by: Papers (25)

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Power system resilience has become a critical topic in recent years because of the increasing trend of extreme events and the growing integration of intermittent renewable energy sources. To enhance grid resilience against high-impact, low-frequency events, two questions should be answered: how to quantify the resilience of a given grid and how to incorporate the quantification into power system p...Show More

Quantitative Metrics for Grid Resilience Evaluation and Optimization

Yiyun Yao;Weijia Liu;Rishabh Jain;Badrul Chowdhury;Jianhui Wang;Robert Cox

IEEE Transactions on Sustainable Energy

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Reliability Evaluation for Integrated Electricity-Gas Systems Considering Hydrogen

Tao Wu;Jianhui Wang

IEEE Transactions on Sustainable Energy

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Cited by: Papers (21)

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Regarded as the cleanest and a versatile energy carrier, green hydrogen generated with renewable energy is receiving increased attention in the transition to a carbon-neutral society. On the other hand, the integration of hydrogen tightens the coupling between power systems and natural gas systems, which highlights the importance of reliability evaluation of the integrated electricity-gas systems ...Show More

Reliability Evaluation for Integrated Electricity-Gas Systems Considering Hydrogen

Tao Wu;Jianhui Wang

IEEE Transactions on Sustainable Energy

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Analytical Derivation of Frequency Response Rate Constraint in Distribution System Restoration With Single Master Diesel-Based DG

Dexiang Lai;Chen Chen;Sijia Tang;Zhaohong Bie;Jianhui Wang

IEEE Transactions on Smart Grid

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Cited by: Papers (2)

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Transient frequency deviation resulting from load pick-up operations is a barrier to DG-based service restoration. The prime mover dynamics and control-parameter configuration have a significant effect on the frequency response rate (FRR) in the restoration process, but have not been sufficiently considered in previous works. To address this issue, this letter analyzes the FRR based on the transfe...Show More

Analytical Derivation of Frequency Response Rate Constraint in Distribution System Restoration With Single Master Diesel-Based DG

Dexiang Lai;Chen Chen;Sijia Tang;Zhaohong Bie;Jianhui Wang

IEEE Transactions on Smart Grid

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Distributionally Robust Decentralized Scheduling Between the Transmission Market and Local Energy Hubs

Shengfei Yin;Jianhui Wang

IEEE Transactions on Power Systems

Year: 2023 | Volume: 38, Issue: 2 | Journal Article |

Cited by: Papers (8)

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The cross impacts between transmission and distribution systems have drawn extensive attention, where multi-energy carriers become increasingly dominant in local market operations. Local energy hubs, integrated with multi-energy carriers, e.g., electricity, gas, heat, present great potentials to provide adequate power and reserve support for the transmission system, which could mitigate issues suc...Show More

Distributionally Robust Decentralized Scheduling Between the Transmission Market and Local Energy Hubs

Shengfei Yin;Jianhui Wang

IEEE Transactions on Power Systems

Year: 2023 | Volume: 38, Issue: 2 | Journal Article |

Distribution Service Restoration With Renewable Energy Sources: A Review

Abdulraheem H. Alobaidi;Seyed Saeed Fazlhashemi;Mahdi Khodayar;Jianhui Wang;Mohammad E. Khodayar

IEEE Transactions on Sustainable Energy

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Cited by: Papers (18)

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Distribution service restoration plays a vital role in mitigating the adverse impacts of power outages stemming from extreme weather conditions. With incentives toward reducing the carbon footprint of power generation on the environment and the reliance on fossil fuel resources, the future distribution networks are equipped with distributed renewable energy sources. This paper reviews the state-of...Show More

Distribution Service Restoration With Renewable Energy Sources: A Review

Abdulraheem H. Alobaidi;Seyed Saeed Fazlhashemi;Mahdi Khodayar;Jianhui Wang;Mohammad E. Khodayar

IEEE Transactions on Sustainable Energy

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

P2P Multigrade Energy Trading for Heterogeneous Distributed Energy Resources and Flexible Demand

Jiayong Li;Daosen Xu;Jianhui Wang;Bin Zhou;Ming-Hao Wang;Lipeng Zhu

IEEE Transactions on Smart Grid

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Cited by: Papers (30)

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This paper proposes a novel peer-to-peer (P2P) multi-grade energy trading design to encourage demand side flexibility to locally absorb the uncertainty of renewable distributed energy resources (DERs) in distribution networks. In particular, a reliability credit (RC) assignment method is developed for customers to differentiate the energy grades considering the heterogeneity in energy supplying re...Show More

P2P Multigrade Energy Trading for Heterogeneous Distributed Energy Resources and Flexible Demand

Jiayong Li;Daosen Xu;Jianhui Wang;Bin Zhou;Ming-Hao Wang;Lipeng Zhu

IEEE Transactions on Smart Grid

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Nested Bilevel Energy Hub Bidding and Pricing With Price-Responsive Demand

Yanling Lin;Jianhui Wang

IEEE Transactions on Smart Grid

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Cited by: Papers (15)

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The increasing interdependence among different energy systems has led to the development of the integrated energy system (IES), where the energy hub (EH) is a primary market player in the distribution-level energy market. In an EH, subsystems such as electric, natural gas, and heating systems coexist and are interdependent. This paper proposes an innovative bilevel strategic decision-making framew...Show More

Nested Bilevel Energy Hub Bidding and Pricing With Price-Responsive Demand

Yanling Lin;Jianhui Wang

IEEE Transactions on Smart Grid

Year: 2023 | Volume: 14, Issue: 2 | Journal Article |

Applications of Physics-Informed Neural Networks in Power Systems - A Review

Bin Huang;Jianhui Wang

IEEE Transactions on Power Systems

Year: 2023 | Volume: 38, Issue: 1 | Journal Article |

Cited by: Papers (140)

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The advances of deep learning (DL) techniques bring new opportunities to numerous intractable tasks in power systems (PSs). Nevertheless, the extension of the application of DL in the domain of PSs has encountered challenges, e.g., high requirement for the quality and quantity of training data, production of physically infeasible/inconsistent solutions, and low generalizability and interpretabilit...Show More

Applications of Physics-Informed Neural Networks in Power Systems - A Review

Bin Huang;Jianhui Wang

IEEE Transactions on Power Systems

Year: 2023 | Volume: 38, Issue: 1 | Journal Article |

Multi-Period Reconfiguration for Unbalanced Distribution Networks with Hydrogen Injection

Anping Zhou;Jianhui Wang

2022 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2022 | Conference Paper |

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The deepening penetration of distributed generation (DG) imposes tremendous challenges on distribution networks. In this paper, we develop a multi-period reconfiguration model for three-phase unbalanced distribution networks with hydrogen injection. A novel power-to-hydrogen-and-heat model is firstly proposed to improve the efficiency of hydrogen production. Then the methanation process and a gas ...Show More

Multi-Period Reconfiguration for Unbalanced Distribution Networks with Hydrogen Injection

Anping Zhou;Jianhui Wang

2022 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2022 | Conference Paper |

On the Integration of Hydrogen Into Integrated Energy Systems: Modeling, Optimal Operation, and Reliability Assessment

Tao Wu;Jianhui Wang;Meng Yue

IEEE Open Access Journal of Power and Energy

Year: 2022 | Volume: 9 | Journal Article |

Cited by: Papers (17)

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The proliferation of renewable energy (RE) brings tremendous challenges to integrated energy systems (IESs). Converting RE into hydrogen, one of the cleanest energy carriers, provides an appealing alternative for decarbonized IESs. Among the various hydrogen applications, blending hydrogen into natural gas systems is already applicable. However, the disparate hydrogen physical properties trigger c...Show More

On the Integration of Hydrogen Into Integrated Energy Systems: Modeling, Optimal Operation, and Reliability Assessment

Tao Wu;Jianhui Wang;Meng Yue

IEEE Open Access Journal of Power and Energy

Year: 2022 | Volume: 9 | Journal Article |

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