Article
Engineering, Electrical & Electronic
Beibei Wang, Ni Tang, Rui Bo, Fangxing Li
Summary: The paper introduces an extension of the DLMP model based on LPF-D, incorporating a three-phase distribution model to form the proposed TDLMP based on TLPF-D. An imbalance cost component is included in this three-phase DLMP model. Case studies demonstrate that VCC and ICC are significant components in the TDLMP, and DERs can reduce the TDLMP, particularly by improving voltages and reducing phase imbalance.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Mengmeng Cai, Rui Yang, Yingchen Zhang
Summary: This article introduces a linear-approximated DLMP for distributed energy resources, which efficiently solves the issue of high computational costs. It also enhances the model's applicability through generalization to 3-phase unbalanced loads and meshed network structures.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Mathematics, Applied
B. Sereeter, A. S. Markensteijn, M. E. Kootte, C. Vuik
Summary: The paper introduces a novel linearized power flow (LPF) technique that is capable of handling both PQ and PV buses, applicable to both transmission and distribution networks. The LPF method significantly reduces computation time while maintaining similar accuracy as nonlinear power flow (NPF) methods. This makes LPF a good alternative to NPF methods in power flow computations.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2021)
Article
Computer Science, Information Systems
Shri Ram Vaishya, Abhijit R. Abhyankar, Partik Kumar
Summary: This article proposes a linearized ACOPF framework and LMP calculation method for efficient and economical scheduling of distributed energy resources and congestion management in active distribution networks. The method takes into account the effects of high R/X ratio and network constraints, and mathematically derives LMPs for the loads.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Rui Cheng, Zhaoyu Wang, Yifei Guo
Summary: This paper proposes an online feedback-based linearized power flow model for tackling the challenges posed by the nonlinear and nonconvex nature of ac power flow in unbalanced distribution networks. By leveraging the instantaneous measurements of voltages and load consumption, the model updates its parameters in real-time, enhancing accuracy and superiority. Furthermore, the paper provides a unified matrix-vector compact form of the model by exploiting the connection structure of unbalanced radial distribution networks.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Energy & Fuels
Ali Asghar Talebi, Mohammad Ebrahim Hajiabadi, Mahdi Samadi, Hossein Lotfi
Summary: This study aims to investigate and quantify the impact of responsive demand on key components of the electricity market, as well as examine the sensitivity of market variables to price-responsive demand parameters.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Engineering, Electrical & Electronic
Hongbin Wang, Niancheng Zhou, Yu Zhang, Jianquan Liao, Shuyin Tan, Xuan Liu, Chunsheng Guo, Qianggang Wang
Summary: This study proposes a linear power flow algorithm to address the voltage unbalance problem in bipolar direct current distribution networks. The algorithm analyzes the structural characteristics of multiple types of flexible equipment, establishes a steady-state model, and proposes a network modeling and power flow calculation method. Through verification cases, the effectiveness of flexible equipment on power quality issues is demonstrated.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Rahul Ranjan Jha, Adedoyin Inaolaji, Biswajit Dipan Biswas, Arun Suresh, Anamika Dubey, Sumit Paudyal, Sukumar Kamalasadan
Summary: In power distribution systems, the optimal power flow (D-OPF) is a non-convex and non-linear programming problem. Convex relaxation and linear approximation models are used for computational efficiency, but they have different assumptions, performance, and may yield physically meaningless solutions. This study compares the performance of second-order cone programming (SOCP), semi-definite programming (SDP), and linear programming (LP) approaches for D-OPF, evaluating their feasibility, optimality, and scalability compared to NLP-based formulations. The study also compares bus injection and branch flow based on NLP formulations. Evaluations are conducted on small, medium, and large distribution feeders, showing that the feasibility and exactness of relaxed D-OPF formulations depend on the problem type, some NLP formulations are more computationally tractable, different NLP formulations can converge to different local solutions, and the linear model may underestimate or overestimate the cost function and lead to AC-infeasible solutions.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Computer Science, Information Systems
Felipe O. S. Saraiva, V. Leonardo Paucar
Summary: This paper proposes an LMP decomposition model based on an OPF framework with a fully distributed slack bus formulation for the implementation of risk hedging instruments. In this model, active and reactive power mismatches are compensated through the conventional active power distributed slack bus and the proposed reactive power distributed slack bus.
Article
Energy & Fuels
Zhaoxiong Huang, Liping Huang, Chun Sing Lai, Youwei Jia, Zhuoli Zhao, Xuecong Li, Loi Lei Lai
Summary: This paper presents an in-depth study of a linearized AC power flow model with reactive power and voltage magnitude. It derives sensitivity factors and proposes a resilience-constrained economic dispatch strategy. An iterative contingency filtering algorithm is proposed to deal with the computational difficulties associated with N-k contingency constraints.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Engineering, Electrical & Electronic
Hanyang Lin, Firdous Ul Nazir, Bikash C. Pal, Ye Guo
Summary: When modernizing urban distribution systems by replacing overhead lines with underground cables, the existence of shunt admittances cannot be ignored. Traditional power flow models and recently proposed linear models are not suitable for fast calculation and optimization in systems with non-negligible line shunts. This paper proposes a linearized branch flow model that considers line shunts, demonstrating improved calculation accuracy and computational efficiency in controlling network voltages.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Automation & Control Systems
Hossein Saber, Mehdi Ehsan, Moein Moeini-Aghtaie, Hossein Ranjbar, Matti Lehtonen
Summary: Designing transactive energy markets for residential prosumers is an important topic, but existing platforms often ignore voltage imbalance issues and lack user-friendly strategies. This article proposes a network-constrained TE model that effectively addresses these problems and decreases voltage imbalance.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Xiaofei Wang, Fangxing Li, Linquan Bai, Xin Fang
Summary: With the adoption of distributed energy resources (DERs), the traditional uniform energy pricing in the electric distribution system is shifting towards a more active distribution network (ADN) operation. A distribution-level electricity market and distribution locational marginal price (DLMP) have been proposed as a solution to efficiently manage the complexities in this transition. This article provides an overview of the current market architectures, reviews the clearing model and DLMP formulation, summarizes the solution methods for distribution market clearing, discusses DLMP applications in DER and DSO operations and planning, and presents future research directions and potential barriers and challenges.
PROCEEDINGS OF THE IEEE
(2023)
Article
Engineering, Electrical & Electronic
Penghua Li, Wenchuan Wu, Xiaoming Wang, Bin Xu
Summary: In this letter, a data-driven linear power flow model that incorporates Kirchhoff's law constraints for distribution networks (DNs) is proposed. The model combines support vector regression (SVR) and ridge regression (RR) algorithms to improve accuracy, especially for optimal power flow (OPF) calculation.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Tiance Zhang, Jianxiao Wang, Gengyin Li, Xuanyuan Wang, Ming Zhou
Summary: This article introduces an efficient projection-based method for characterizing the feasible region of active distribution networks with temporal-coupled constraints. By formulating the problem as a max-min optimization program and transforming it into a solvable mixed-integer linear programming, the method accurately describes the feasible region under large-scale temporal-coupled constraints.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Xiaofei Wang, Fangxing Li, Qiwei Zhang, Qingxin Shi, Jinning Wang
Summary: This paper proposes a two-stage stochastic bilevel programming model for allocating battery energy storage systems (BESSs) optimally. The first stage determines the optimal siting and sizing of BESSs within a limited budget, while the second stage maximizes arbitrage revenue and clears the distribution market. The model is transformed into a tractable two-stage stochastic mixed-integer linear programming model using KKT optimality conditions, strong duality theory, and the big-M method. A statistics-based scenario extraction algorithm is used to generate typical operating scenarios, and scale reduction strategies for BESS candidate buses and inactive voltage constraints are proposed to reduce model size. Case studies on IEEE 33-bus and 123-bus systems validate the effectiveness of the model and the proposed scale reduction strategies.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Electrical & Electronic
Changjiang Wang, Xiao Kou, Tao Jiang, Houhe Chen, Guoqing Li, Fangxing Li
Summary: Recent studies have found that support vector machine is a promising approach for predicting the transient stability of power systems. However, existing methods often suffer from excessive training time and low robustness, leading to inefficiency in implementation. This paper presents a novel TSA method that addresses these issues by using sequential minimal optimization based support vector machine with pinball loss. The proposed method achieves high accuracy, robustness, and computational efficiency in bulk power grids, as demonstrated by simulation results with the IEEE 50-machine test system and the China Southern Power Grid.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Jiaxin Wen, Siqi Bu, Fangxing Li
Summary: This paper proposes two-level ensemble methods to efficiently assess the risk of maximal frequency deviation (MFD) caused by stochastic outputs of multiple renewable energy sources (RESs). The first level method (PAM-CH) enables fast evaluation and visualization of MFD risk using partitioning around medoids (PAM) and convex hull (CH). The second level method (DBSCAN-PAM) further assesses MFD risk based on varying distributions and correlations of RES outputs using density-based spatial clustering (DBSCAN) and PAM. The accuracy and efficiency of the proposed methods are validated in benchmark systems and a real provincial power grid.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Qinran Hu, Zishan Guo, Fangxing Li
Summary: Production cost minimization (PCM) simulation is an important tool for long-term power system simulation and assessment. However, solving PCM problems is time-consuming due to numerous binary variables. Additionally, the slow solution speed of PCM problems cannot meet the requirement for quick assessment of various planning options in modern energy systems. Most previous works on accelerating PCM problems provide approximate solutions without considering the importance of accurate solutions. Thus, this work proposes a fast PCM simulation method based on imitation learning, which guarantees optimality. Compared with the popular open-source solver SCIP, the proposed method can find the optimal solution faster or provide a smaller gap within the preset solving time limit. Simulation results demonstrate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Hang Shuai, Fangxing Li, Buxin She, Xiaofei Wang, Jin Zhao
Summary: This paper investigates the optimal routing of utility vehicles to restore outages in the distribution grid as fast as possible after a storm. An AlphaZero based utility vehicle routing approach is developed to achieve the real-time dispatching of the repair crews and simulation results show that the proposed approach can efficiently navigate crews to repair all outages.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Mingshen Wang, Xue Li, Chaoyu Dong, Yunfei Mu, Hongjie Jia, Fangxing Li
Summary: This paper proposes a DA optimal bidding model that addresses the temporal distribution, charging and discharging management, and bidding curves for retailers managing electric vehicles. The model covers all connecting periods of EVs that may impact the power demand prediction and incorporates incentive mechanisms for charging and discharging. Simulations validate the proposed model.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Electrical & Electronic
Chenggang Mu, Tao Ding, Shanying Zhu, Ouzhu Han, Pengwei Du, Fangxing Li, Pierluigi Siano
Summary: In this paper, a decentralized market model integrating electricity and carbon emission rights (CER) trading is established for a microgrid. The proposed model satisfies transaction demand and ensures the carbon emission constraint. Energy storage is introduced for load balancing, and a fully distributed algorithm is designed to solve global constraints locally. The algorithm reduces cost, ensures transparency, and has been proven to be convergent. Numerical results validate the effectiveness of the proposed market model.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Electrical & Electronic
Xiaofei Wang, Fangxing Li, Linquan Bai, Xin Fang
Summary: With the adoption of distributed energy resources (DERs), the traditional uniform energy pricing in the electric distribution system is shifting towards a more active distribution network (ADN) operation. A distribution-level electricity market and distribution locational marginal price (DLMP) have been proposed as a solution to efficiently manage the complexities in this transition. This article provides an overview of the current market architectures, reviews the clearing model and DLMP formulation, summarizes the solution methods for distribution market clearing, discusses DLMP applications in DER and DSO operations and planning, and presents future research directions and potential barriers and challenges.
PROCEEDINGS OF THE IEEE
(2023)
Article
Engineering, Electrical & Electronic
Hantao Cui, Stavros Konstantinopoulos, Denis Osipov, Jinning Wang, Fangxing Li, Kevin L. Tomsovic, Joe H. Chow
Summary: This article examines the impact of high penetration of converter-interfaced renewable energy resources on the swing dynamics between synchronous generators in power systems. The study shows that as the penetration level of constant-power grid-following converters increases, the speed of disturbance propagation increases due to reduced system inertia. Converters with the ability to positively respond to disturbances can slow down the propagation speed.
PROCEEDINGS OF THE IEEE
(2023)
Article
Green & Sustainable Science & Technology
Hongji Zhang, Tao Ding, Yuge Sun, Yuhan Huang, Yuankang He, Can Huang, Fangxing Li, Chen Xue, Xiaoqiang Sun
Summary: This study provides a comprehensive analysis of the impacts of load-side re-electrification options on decarbonization pathways and transition costs within energy systems. The findings suggest that extensive load-side re-electrification can potentially achieve a maximum carbon dioxide emission reduction of up to 37.15% by 2060, without the deployment of carbon dioxide removal technologies.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Review
Engineering, Electrical & Electronic
Buxin She, Fangxing Li, Hantao Cui, Jingqiu Zhang, Rui Bo
Summary: This paper provides a comprehensive review of microgrid control with the fusion of model-free reinforcement learning (MFRL) in the context of emerging large-scale distributed energy resources (DERs) and advanced control techniques. The research map of microgrid control is developed from six distinct perspectives, and the configurations of grid-following (GFL) and grid-forming (GFM) inverters are illustrated. The integration of MFRL into the existing control framework is explained, along with the application guideline and discussion of fusing approaches. The fundamental challenges and corresponding insights for addressing them are also fully discussed.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Energy & Fuels
Qiwei Zhang, Fangxing Li, Linquan Bai, Honggang Wang, Jin Zhao, Hang Shuai
Summary: This paper investigates the benefits of multienergy system (MES) operation on energy usage flexibility and efficiency. Six properties of the locational marginal prices (LMP) in MES market-clearing models are identified, and two new types of critical load levels (CLL) are defined and discussed. Grey relation analysis (GRA) is used to quantify the CLLs and analyze the coupling of MES from LMP patterns. The proposed analysis is demonstrated with small and large MES case studies.
IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY
(2023)
Article
Automation & Control Systems
Ouzhu Han, Tao Ding, Chenggang Mu, Wenhao Jia, Zhoujun Ma, Fangxing Li
Summary: This paper proposes a two-stage scheduling model for data center operators (DCOs) and the system operator (SO) in demand response (DR) implementations. In the DR scheduling, the SO formulates DR compensation prices while each DCO decides its best-response power demands. A two-stage DR Stackelberg game model is proposed, with a Kriging-metamodel-based algorithm to protect the data privacy of DCOs.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Information Systems
Helia Zandi, Michael Starke, Chris Winstead, Teja Kuruganti, Justin Hill, Fangxing Li
Summary: Substantial investments have been made in researching and developing concepts and technologies to support smart grid, renewable integration, and grid-interactive buildings in the past decade. The integration of solar photovoltaics with energy storage in residential buildings is increasing due to the economic and resilience benefits. Effective integration and control of these systems are critical for improving building energy efficiency, reducing carbon footprint, and supporting grid resiliency.
Article
Computer Science, Information Systems
Jiaqi Zhao, Hanzheng Wang, Yong Zhou, Rui Yao, Silin Chen, Abdulmotaleb El Saddik
Summary: This paper proposes a discriminative feature learning network based on a visual Transformer for VI-ReID. By using a spatial feature awareness module and a channel feature enhancement module, the network captures long-term dependencies and improves feature representation. Experimental results demonstrate the significant advantages of the proposed method in VI-ReID tasks.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
