Article
Energy & Fuels
Yu Zhou, Zhengshuo Li, Guangrui Wang
Summary: This paper suggests leveraging the reactive power range embedded in wind farms to improve safety and optimality during the power system reactive power optimization process. An uncertain reactive power optimization problem involving wind farm reactive power range is introduced, which is recast as a deterministic optimization problem. The study confirms that wind farms are competent reactive power resources even with notable uncertainty.
Article
Energy & Fuels
Dundun Liu, Shenxi Zhang, Haozhong Cheng, Lu Liu, Zheng Wang, Da Sang, Ruijin Zhu
Summary: This paper proposes a robust ESS planning model to accommodate uncertain wind power investment and coal-fired unit retirement. By considering the uncertainties of unit retirement and wind power investment, a better trade-off between ESS investment cost and operational cost is achieved.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Zipeng Liang, Haoyong Chen, Simin Chen, Yongchao Wang, Cong Zhang, Chongqing Kang
Summary: This study proposes a novel adaptive optimization method to optimize the value of the uncertainty budget and minimize the size of the uncertainty set, while considering the risk of wind power generation fluctuations. The method achieves a good tradeoff between robustness and costs in transmission expansion planning.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Automation & Control Systems
Youngchae Cho, Takayuki Ishizaki, Jun-Ichi Imura
Summary: In order to ensure power supply-demand balance with increasing wind power penetration, a new nonanticipative robust unit commitment model (NRUC) is proposed in this article. It addresses three decision-making problems under different levels of uncertainty by delaying the determination of dispatch policy until uncertainty decreases. Results from simulations on test systems show that the proposed NRUC outperforms existing models in terms of feasibility and optimality under current but decreasing wind power uncertainty.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Zhicheng Jiang, Qingguang Yu, Le Li, Yuming Liu
Summary: The paper discusses the development direction and optimization methods of offshore multiplatform interconnected power systems with wind power, introducing cable size selection variables and linearization of the model to improve accuracy and efficiency of planning schemes.
Article
Engineering, Electrical & Electronic
Yuan Chi, Yan Xu, Rui Zhang
Summary: This paper proposes a robust dynamic VAR planning method to enhance the voltage stability of wind energy power systems under uncertainty, considering uncertainties from wind power output and STATCOMs initial state. A multi-objective optimization problem is solved using Adaptive Non-dominated Sorting Genetic Algorithm-III based on Latin Hypercube Sampling, showing higher computational efficiency and robust optimality compared to conventional methods.
IEEE TRANSACTIONS ON POWER DELIVERY
(2021)
Article
Computer Science, Information Systems
Yang Liu, Tianyu Liu
Summary: The P2G technology enables the storage of electric energy in the form of natural gas, deepening the coupling between power and natural gas systems, leading to the emergence of an integrated energy system with the power grid at its core. A collaborative planning method based on non-cooperative game theory is proposed to address uncertainties in planning and optimize interests of manufacturers in the gas-electric system.
Review
Energy & Fuels
A. A. Ghadimi, M. Gholami, M. R. Miveh
Summary: Conventional energy resource problems have led to increased utilization of renewable energy sources (RESs) in power systems. Wind power generation is a promising solution, but it can lead to voltage problems, stability issues, system losses, and line congestions. This paper reviews the optimization techniques that apply Flexible Alternating Current Transmission Systems (FACTS) devices to accelerate wind energy integration.
ENERGY SCIENCE & ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Zhenjia Lin, Qiuwei Wu, Haoyong Chen, Tianyao Ji, Yinliang Xu, Hongbin Sun
Summary: A novel scenarios-oriented distributionally robust optimization (DRO) model is proposed for the energy and reserve scheduling (ERS) problem. The worst-case distribution of DRO is interpreted as extreme scenarios (ESs) with their own weights, which are described using the taguchi's orthogonal array testing (TOAT) method. The proposed scenarios-oriented DRO (SDRO) model has better engineering practicality and can guarantee the optimality of expected cost under the worst-case distribution and the feasibility of all possible wind power generation.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Yunhui Shi, Shufeng Dong, Chuangxin Guo, Zhe Chen, Luyu Wang
Summary: The paper introduces a multi-stage robust program to address the real-time economic dispatch problem, which can better utilize energy storage systems and mitigate the risk of high costs.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Thermodynamics
Felipe Verastegui, Alvaro Lorca, Daniel Olivares, Matias Negrete-Pincetic
Summary: Several countries are adopting plans to reduce contaminant emissions from the energy sector through renewable energy integration and restrictions on fossil fuel generation. This study develops a planning model that includes an effective representation of the system's operational aspects to understand the key role of flexible resources in highly renewable power systems undergoing strong decarbonization. The results show that highly renewable generation mixes are feasible with an effective balance of flexibility attributes like ramping, storage, and transmission capacities.
Article
Green & Sustainable Science & Technology
Yachao Zhang, Wei Liu, Zhanghao Huang, Feng Zheng, Jian Le, Shu Zhu
Summary: The advancement of dynamic wireless charging technology for electric vehicles has led to the development trend of electrified transportation systems, prompting the need for a coordinated operational model. A distributionally robust optimization (DRO) model is proposed to comprehensively address uncertainties in multi-energy coupled systems, resulting in cost savings and improved decision-making for system reliability and economy.
Article
Energy & Fuels
Yang Fu, Yang Liu, Ling-ling Huang, Feixiang Ying, Fangxing Li
Summary: This paper investigates the issue of wind power curtailment in DC series-parallel collection systems and proposes an optimization model considering this problem. An improved algorithm is used to solve the optimization problem, and the proposed model and algorithm are tested on a deep-sea offshore wind farm. The results show that considering wind power curtailment can save long-term cable costs, and aligning the wiring direction perpendicular to the prevailing wind direction helps increase power generation and reduce costs.
IEEE TRANSACTIONS ON ENERGY CONVERSION
(2022)
Article
Engineering, Marine
Lele Ma, Xiaobing Kong, Xiangjie Liu, Mohamed Abdelkarim Abdelbaky, Ahmad H. Besheer, Mingyu Wang, Kwang Y. Lee
Summary: In this paper, a robust economic model predictive control (EMPC) strategy is developed to minimize damage to the turbine while maximizing electric power output in the offshore wind power generation system. A linear model is used to approximate the nonlinear behavior of the system, and a linear feedback controller is designed to restrict the deviation between the nominal linear system and the actual nonlinear system. Plant simulations and NREL FAST code testing demonstrate the effectiveness of the proposed controller throughout the operating region.
Article
Thermodynamics
Allah Rakhio Junejo, Nauman Ullah Gilal, Jaehyeok Doh
Summary: This study focuses on the design of wind turbine in urban environments, using a vertical-axis wind turbine. The design of the robust control system becomes challenging due to the nonlinear aerodynamic characteristics of the rotor blades. By using the proposed controller and a low-inertia turbine, there is a substantial active power gain of approximately 25% compared to traditional control systems.
Article
Engineering, Electrical & Electronic
Chao Shen, Zhikang Shuai, Yang Shen, Yelun Peng, Xuan Liu, Zuyi Li, Z. John Shen
Summary: This article investigates the advantages and challenges of paralleled current-controlled voltage source converters and virtual synchronous generators system in providing power and voltage/frequency regulation. By establishing a mathematical model and conducting theoretical analysis, a control method to improve transient stability of the system is proposed, showing better performance compared to traditional methods. The impact of CCS capacity on VSG transient stability is also discussed, with validation through Lyapunov's method and simulation/experimental results.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Engineering, Electrical & Electronic
Hong Wang, Linhai Qi, Lei Yan, Zuyi Li
Summary: This article introduces a novel load analysis method called Load Photo, which creates image matrices for various loads in power systems using the HSV color space, making it compatible with deep learning models. Load photos represent loads as 2-D pixel graphical representations and store load-related parameters, allowing for characterization of load energy consumption patterns.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Engineering, Electrical & Electronic
Yiwei Qiu, Jin Lin, Feng Liu, Ningyi Dai, Yonghua Song
Summary: This paper presents a systematic approach based on stochastic differential equations to model the continuous random processes of AGC signals, capturing their special characteristics. Simulation results show that this method accurately captures the probability distribution and temporal correlation.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Zhaojian Wang, Feng Liu, Zhiyuan Ma, Yue Chen, Mengshuo Jia, Wei Wei, Qiuwei Wu
Summary: This paper proposes a distributed approach to solving the Generalized Nash equilibrium (GNE) of the energy sharing game, by proving the strong monotonicity of the game and converting the GNG into an equivalent optimization problem. An algorithm based on Nesterov's methods is used to solve the equivalent problem and find the GNE in a distributed manner. The algorithm's convergence is rigorously proven based on the nonexpansive operator theory, and its performance is validated through experiments with three prosumers and scalability tested with simulations using 1888 prosumers.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Thermodynamics
Fangyun Bai, Xinglong Ju, Shouyi Wang, Wenyong Zhou, Feng Liu
Summary: This paper presents an improved algorithm for wind farm layout optimization. By transforming the relocation of multiple wind turbines into a single-player reinforcement learning problem and utilizing Monte-Carlo Tree Search, significant improvement is achieved compared to previous algorithms.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Engineering, Electrical & Electronic
Jiarong Li, Jin Lin, Philipp Heuser, Heidi Heinrichs, Jinyu Xiao, Feng Liu, Martin Robinius, Yonghua Song, Detlef Stolten
Summary: This paper proposes a co-planning approach for regional wind resources-based ammonia industry and the electric network, which can significantly enhance wind power utilization and reduce total investment costs. The siting and operation flexibility of PtA can reduce the expansion burden of EN, as demonstrated by the experiment.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Xiuqiang He, Changjun He, Sisi Pan, Hua Geng, Feng Liu
Summary: This paper investigates the synchronization stability of inverter-based generation (IBG) during asymmetrical faults. A dual-sequence synchronization model for IBG is developed and the possible types of synchronization instability and their dominant factors are identified through quantitative analysis. The model and analysis are validated through simulations and hardware-in-the-loop experiments.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Yunfan Zhang, Feng Liu, Zhaojian Wang, Yifan Su, Weisheng Wang, Shuanglei Feng
Summary: This paper proposes a novel stochastic adaptive robust optimization model for determining the optimal self-scheduling plan for virtual power plants in the day-ahead energy-reserve market. By aggregating renewable generation units, conventional power plants, energy storages, and flexible demands, virtual power plants provide a flexible solution to distributed energy resources integration.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Min Chen, Ciwei Gao, Mohammad Shahidehpour, Zuyi Li
Summary: This paper proposes an aggregation method for proliferated small-size data networks to apply data networks' spatial load regulation potentials for demand response. The method models each data network as a virtual power network and proposes an aggregated virtual power network (AVPN) for multiple virtual power networks. The paper also formulates supply curves representing AVPN DR to capture the regulation costs of virtual power networks.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Runhai Jiao, Yanzhi Liu, Hui He, Xuehai Ma, Zuyi Li
Summary: In this paper, a deep neural network model named Camp-Net is proposed for detecting bolt defects in transmission tower images, using multi-scale features and context information. Experimental results show that the proposed model can accurately identify loose pins and bolts without pins, with a higher detection accuracy compared to the commonly used high performance model.
IEEE TRANSACTIONS ON POWER DELIVERY
(2022)
Article
Engineering, Electrical & Electronic
Min Du, Xuan Liu, Quan Zhou, Zuyi Li
Summary: This paper proposes a hybrid robust tri-level defender-attacker-defender (DAD) model to mitigate the multi-period attack risk in modern power systems. The model integrates the N-K criterion and attack scenario uncertainties to provide a resilient defense strategy. It also considers the optimal allocation of offensive resources during multi periods of an attack to develop a more practical defense strategy. The column-and-constraint generation algorithm is applied to derive its optimal solutions.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Engineering, Electrical & Electronic
Lei Yan, Wei Tian, Jiayu Han, Zuyi Li
Summary: This research proposes an event-based Hidden Markov model for load disaggregation of multiple appliances in households, integrating transient signatures into mathematical formula. The model achieves real-time accurate load disaggregation by utilizing high-resolution data and outperforms other state-of-the-art variants in both computational time and accuracy on the tested dataset.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Energy & Fuels
Guangyu He, Jucheng Xiao, Shuai Fan, Zuyi Li
Summary: This study proposes a new substitute energy price market mechanism to address the incompatibility of current electricity market mechanisms. By introducing a substitute energy price, energy curves can be traded as substitutes, and regulation energy is introduced as tradable commodities to adapt to the needs of renewable energy and energy storage.
Article
Engineering, Electrical & Electronic
Min Du, Xuan Liu, Zuyi Li, Hai Lin
Summary: In this paper, a robust mitigation strategy model is proposed to reduce the risk of dummy data attacks (DDAs). By preventing the attacker from constructing high-stealth attack scenarios, the model secures line flow levels while balancing the economy and security of power systems. A novel decomposition algorithm is developed to solve the proposed model, guaranteeing solution optimality in a finite number of iterations. Simulation results on the IEEE 118-bus and Chinese 132-bus systems demonstrate the effectiveness of the approach.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Green & Sustainable Science & Technology
Luomeng Zhang, Hongxing Ye, Fei Ding, Zuyi Li, Mohammad Shahidehpour
Summary: Physical constraints are necessary for integrating distributed energy resources, specifically PV, into the distribution network. The concept of hosting capacity (HC) is introduced to determine the maximum renewable energy generation that the distribution system can accommodate. This study proposes a hybrid adjustable power flow model to enhance the HC and effectively utilize flexible resources in a secure and cost-efficient manner. A novel hybrid relaxation approach is presented to convexify a two-stage AC model with variable uncertainty sets, and an iterative algorithm is developed to solve the problem. Case studies on a single-phase 141-node system and a three-phase 33-bus system demonstrate the promising performance of the proposed approach in terms of accuracy, convergence, and robustness.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
