Article
Green & Sustainable Science & Technology
Hassan Shokouhandeh, Mehrdad Ahmadi Kamarposhti, Ilhami Colak, Kei Eguchi
Summary: The proposed new method MGWO successfully solves the unit commitment problem in power systems with uncertainty, with simulation results confirming its superiority over the previous GWO and PSO algorithms.
Article
Engineering, Electrical & Electronic
Jinghua Li, Shuang Zhou, Yifu Xu, Mengshu Zhu, Liu Ye
Summary: This paper introduces a new robust optimization model called multi-band uncertainty robust optimization, which aims to better balance the robustness and economy of power systems with wind energy. By dividing the wind power fluctuation interval into smaller intervals and adjusting the parameter setting method based on historical wind power samples, the proposed multi-band uncertainty robust optimization shows better performance in balancing the system's robustness and economy compared to classical robust optimization and Seng-Cheol Kang robust optimization.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Xin Wen, Dhaker Abbes, Bruno Francois
Summary: This paper investigates the impact of photovoltaic power production uncertainty on generation scheduling in power systems, using a dynamic programming algorithm to solve a non-convex mixed-integer nonlinear programming model, and analyzing the cost and operational reserve variations due to PV power uncertainty.
MATHEMATICS AND COMPUTERS IN SIMULATION
(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
Engineering, Electrical & Electronic
Jianqiang Luo, Fei Teng, Siqi Bu, Zhongda Chu, Ning Tong, Anbo Meng, Ling Yang, Xiaolin Wang
Summary: This paper proposes a solution to address the traditional operational constraint issue in power systems considering converter-driven stability and elaborates on a power sensitivity-based power dispatch method to enhance stability margin and update operational constraint solutions.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Green & Sustainable Science & Technology
Tong Wu, Ying-Jun Angela Zhang, Shuoyao Wang
Summary: This paper proposes a new model for scenario-based security-constrained unit commitment (SCUC) with BESSs and solves it using a mixed-integer programming and convolutional neural network algorithm. The algorithm eliminates the need for explicitly considering the scenario-based security constraints, greatly reducing computational complexity and achieving promising results.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Green & Sustainable Science & Technology
Yixun Xue, Mohammad Shahidehpour, Zhaoguang Pan, Bin Wang, Quan Zhou, Qinglai Guo, Hongbin Sun
Summary: This paper proposes a unit commitment considering combined electricity and reconfigurable heating network to coordinate the day-ahead scheduling of power system and district heating system. By reconfiguring the heat supply to enhance the flexibility of the power system, the model is formulated as a nonlinear and mixed-integer model considering the reconfigurable DHN. Through modeling and approximation, computational burdens are significantly reduced. Extensive case studies validate the effectiveness of the model and illustrate the potential benefits of the proposed method for congestion management and wind power accommodation.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2021)
Article
Engineering, Electrical & Electronic
Rui Chen, Deping Ke, Yuanzhang Sun, C. Y. Chung, Haotian Wu, Siyang Liao, Jian Xu, Congying Wei
Summary: This paper proposes a frequency-dependent chance constrained unit commitment (FDCCUC) model that utilizes the operational frequency as a dispatching variable to enhance the load frequency damping (LFD) effect in wind-integrated power systems. The model allows load power to act as a supplemental reserve to upgrade the wind power accommodation capability of the system. A hierarchically implemented searching algorithm is also proposed to protect private scheduling information in a bulk AC/DC hybrid power system. Simulation results validate the effectiveness of the FDCCUC model and hierarchical searching algorithm.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Green & Sustainable Science & Technology
Akshay Ajagekar, Fengqi You
Summary: This work proposes a deep reinforcement learning (DRL) based approach to address the uncertainties in renewable energy and fluctuating electricity demand, and provide reliable and cost-effective generation schedules of power systems. The approach relies on historical uncertainty realizations and forecast data, and guarantees a feasible commitment schedule without operational constraint violations through safe exploration. Computational experiments on IEEE 39-bus and 118-bus test cases show that the proposed approach outperforms existing methods in terms of computational efficiency and incurred operational costs.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Green & Sustainable Science & Technology
Akshay Ajagekar, Fengqi You
Summary: This paper proposes a deep reinforcement learning approach for the day-ahead scheduling of generation resources under demand and wind power uncertainties. The approach is trained with an actor-critic-based reinforcement learning algorithm and guarantees a feasible commitment schedule without violating operational constraints. Experimental results show that the proposed approach outperforms existing approaches in terms of computational efficiency and operational costs.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Computer Science, Artificial Intelligence
Jinhao Shi, Bo Wang, Ran Yuan, Zhi Wang, Chunlin Chen, Junzo Watada
Summary: The growing use of renewable energy has posed significant challenges to the operation of modern power systems. Academic research and industrial practice have shown that adjusting unit commitment (UC) scheduling periodically based on new forecasts of renewable power can improve system stability and economy. However, this increases the computational burden. This paper proposes a deep reinforcement learning (DRL) method for obtaining timely and reliable solutions for rolling-horizon UC (RHUC). According to experimental results, the proposed algorithm reduces power system operation cost by at least 1.1% in a considerably shorter time compared to traditional methods.
APPLIED INTELLIGENCE
(2023)
Article
Engineering, Electrical & Electronic
Zhenjia Lin, Haoyong Chen, Qiuwei Wu, Jianping Huang, Mengshi Li, Tianyao Ji
Summary: This paper proposes a novel data-adaptive robust unit commitment model under high penetration of wind power, which formulates a joint probabilistic distribution function to capture the correlation of power outputs among multiple wind farms and derive a more practical uncertainty set. By introducing the synchronous characteristic of wind power fluctuation, the proposed model demonstrates effectiveness in handling wind power uncertainties.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Computer Science, Information Systems
Shubin Wang, Xinni Liu, Junsheng Ha
Summary: This article proposes a blockchain-based architecture for the optimal scheduling of the dispatchable units in the smart grids considering the high penetration of renewable energy sources. The proposed method uses blockchain technology to secure data exchange and avoid unauthorized access in the smart grid. The model also considers the reconfiguration problem using remote control switches.
Article
Thermodynamics
Jizhe Dong, Shunjie Han, Xiangxin Shao, Like Tang, Renhui Chen, Longfei Wu, Cunlong Zheng, Zonghao Li, Haolin Li
Summary: The study proposes a method to calculate spinning reserve requirements based on historical virtual wind power data to improve the local adaptability of unit commitment. Application and comparison studies on two systems demonstrate the effectiveness and cost benefits of the method, while sensitivity analyses of different parameters used in the method are also investigated.
Article
Engineering, Electrical & Electronic
Mansour Hosseini-Firouz, Asef Alemi, Behruz Alefy, Shahzad Balalpour
Summary: This study analyzes the relationship between wind power uncertainty and system operating costs, finding a way to balance optimal solutions and risk aversion through multi-objective optimization. By establishing conditional value-at-risk, the study achieves adequate trade-offs in the worst-case scenarios of wind power uncertainty.
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Kazem Khalkhali, Saeed Abapour, Seyed Masoud Moghaddas-Tafreshi, Mehdi Abapour
IET GENERATION TRANSMISSION & DISTRIBUTION
(2015)
Article
Computer Science, Artificial Intelligence
Hamid Hasanzadehfard, Sayed Masoud Moghaddas-Tafreshi, Seyed Mehdi Hakimi
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
(2015)
Article
Engineering, Electrical & Electronic
Seyed Masoud Moghaddas Tafreshi, Azim Saliminia Lahiji
IEEE TRANSACTIONS ON SMART GRID
(2015)
Review
Green & Sustainable Science & Technology
Seyed Masoud Moghaddas Tafreshi, Hassan Ranjbarzadeh, Mehdi Jafari, Hamid Khayyam
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2016)
Article
Engineering, Electrical & Electronic
Azim Saliminia Lahiji, Seyed Masoud Moghaddas Tafreshi
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2016)
Article
Construction & Building Technology
Soheil Mohseni, Seyed Masoud Moghaddas-Tafreshi
SUSTAINABLE CITIES AND SOCIETY
(2018)
Article
Multidisciplinary Sciences
Reza Roofegari Nejad, Seyed Masoud Moghaddas Tafreshi
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2014)
Article
Green & Sustainable Science & Technology
M. Shahverdi, S. M. Moghaddas-Tafreshi, Michael S. Mazzola, A. K. Kaviani
Article
Computer Science, Artificial Intelligence
Kiamars Kaveh, Seyed Mehdi Hakimi, Seyed Masoud Moghaddas-Tafreshi, Fazllolah Naseri
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
(2014)
Article
Engineering, Electrical & Electronic
S. M. Hakimi, S. M. Moghaddas-Tafreshi
IEEE TRANSACTIONS ON SMART GRID
(2014)
Article
Engineering, Electrical & Electronic
Mohammad Javad Salehpour, S. M. Moghaddas Tafreshi
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2019)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Payam Farhadi, Seyyed Masoud Moghaddas Tafreshi
2019 7TH INTERNATIONAL ISTANBUL SMART GRIDS AND CITIES CONGRESS AND FAIR (ICSG ISTANBUL 2019)
(2019)
Article
Engineering, Electrical & Electronic
R. Roofegari Nejad, S. M. Hakimi, S. M. Moghaddas Tafreshi
JOURNAL OF ELECTRICAL SYSTEMS
(2016)
Article
Energy & Fuels
R. Roofegari Nejad, S. M. Hakimi, S. M. Moghaddas Tafreshi
JOURNAL OF ENERGY STORAGE
(2016)
Article
Engineering, Electrical & Electronic
Wandry R. Faria, Gregorio Munoz-Delgado, Javier Contreras, Benvindo R. Pereira Jr
Summary: This paper proposes a new bilevel mathematical model for competitive electricity markets, taking into account the participation of distribution systems operators. A new pricing method is introduced as an alternative to the inaccessible dual variables of the transmission system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Chao Zhang, Liwei Zhang, Dong Wang, Kaiyuan Lu
Summary: The load disturbance rejection ability of electrical machine systems is crucial in many applications. Existing studies mainly focus on improving disturbance observers, but the speed response control during the transient also plays a significant role. This paper proposes a sliding mode disturbance observer-based load disturbance rejection control with an adaptive filter and a Smith predictor-based speed filter delay compensator to enhance the transient speed response.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Arif Hussain, Arif Mehdi, Chul-Hwan Kim
Summary: The proposed scheme in this research paper is a communication-less islanding detection system based on recurrent neural network (RNN) for hybrid distributed generator (DG) systems. The scheme demonstrates good performance in feature extraction, feature selection, and islanding detection, and it also performs effectively in noisy environments.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Zonghui Sun, Xizheng Guo, Shinan Wang, Xiaojie You
Summary: This paper presents a status pre-matching method (SPM) that eliminates the iterative calculations for resistance switch model, and simulates all operation modes of PECs through a more convenient approach. Furthermore, a FPGA implementation scheme is proposed to fully utilize the multiplier units of FPGA.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Rui Zhou, Shuheng Chen, Yang Han, Qunying Liu, Zhe Chen, Weihao Hu
Summary: In power system scheduling with variable renewable energy sources, considering both spatial and temporal correlations is a challenging task due to the complex intertwining of spatiotemporal characteristics and computational complexity caused by high dimensionality. This paper proposes a novel probabilistic spatiotemporal scenario generation (PSTSG) method that generates probabilistic scenarios accounting for spatial and temporal correlations simultaneously. The method incorporates Latin hypercube sampling, copula-importance sampling theory, and probability-based scenario reduction technique to efficiently capture the spatial and temporal correlation in the dynamic optimal power flow problem. Numerical simulations demonstrate the superiority of the proposed approach in terms of computational efficiency and accuracy compared to existing methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Juan Manuel Mauricio, J. Carlos Olives-Camps, Jose Maria Maza-Ortega, Antonio Gomez-Exposito
Summary: This paper proposes a simplified thermal model of VSC, which can produce accurate results at a low computational cost. The model consists of a simple first-order thermal dynamics system and two quadratic equations to model power losses. A methodology is also provided to derive the model parameters from manufacturer data.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Jae-Kyeong Kim, Kyeon Hur
Summary: This paper investigates the relationship between the accuracy of finite difference-based trajectory sensitivity (FDTS) analysis and the perturbation size in non-smooth systems. The study reveals that the approximation accuracy is significantly influenced by the perturbation size, and linear approximation is the most suitable method for practical applications.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yuan Si, Amjad Anvari-Moghaddam
Summary: This paper investigates the impact of geomagnetic disturbances on small signal stability in power systems and proposes the installation of blocking devices to mitigate the negative effects. Quantitative evaluation reveals that intense geomagnetic disturbances significantly increase the risk of small signal instability. Optimal placement of blocking devices based on sensitivity scenarios results in a significant reduction in the risk index compared to constant and varying induced geoelectric fields scenarios.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xuejian Zhang, Wenxin Kong, Nian Yu, Huang Chen, Tianyang Li, Enci Wang
Summary: The intensity estimation of geomagnetically induced currents (GICs) varies depending on the method used. The estimation using field magnetotelluric (MT) data provides the highest accuracy, followed by the estimation using 3D conductivity models and the estimation using a 1D conductivity model. The GICs in the North China 1000-kV power grid have reached a very high-risk level, with C3 and C4 having a significant impact on the geoelectric field and GICs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yue Pan, Shunjiang Lin, Weikun Liang, Xiangyong Feng, Xuan Sheng, Mingbo Liu
Summary: This paper introduces the concept and model of offshore-onshore regional integrated energy system, and proposes a stochastic optimal dispatch model and an improved state-space approximate dynamic programming algorithm to solve the model. The case study demonstrates the effectiveness and high efficiency of the proposed method in improving economic and environmental benefits.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Mohammad Eydi, Reza Ghazi, Majid Oloomi Buygi
Summary: Proportional current sharing, voltage restoration, and SOCs balancing in DC microgrid control algorithms are the leading challenges. This paper proposes a novel communication-less control method using a capacitor and a DC/DC converter to stabilize the system and restore the DC bus voltage. The method includes injecting an AC signal into the DC bus, setting the current of energy storage units based on frequency and SOC, and incorporating droop control for system stability. Stability analysis and simulation results validate the effectiveness of the proposed method.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xiangjian Meng, Xinyu Shi, Weiqi Wang, Yumin Zhang, Feng Gao
Summary: With the increasing penetration of photovoltaic power generation, regional power forecasting becomes critical for stable and economical operation of power systems. This paper proposes a minute-level regional PV power forecasting scheme using selected reference PV plants. The challenges include the lack of complete historical power data and the heavy computation burden. The proposed method incorporates a novel reference PV plant selection method and a flexible approach to decrease the accumulated error of rolling forecasting.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Huabo Shi, Yuhong Wang, Xinwei Sun, Gang Chen, Lijie Ding, Pengyu Pan, Qi Zeng
Summary: This article investigates the dynamic stability characteristics of the full size converter variable speed pumped storage unit and proposes improvements for the control strategy. The research is important for ensuring the safe and efficient operation of the unit.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Firmansyah Nur Budiman, Makbul A. M. Ramli, Houssem R. E. H. Bouchekara, Ahmad H. Milyani
Summary: This paper proposes an optimal harmonic power flow framework for the daily scheduling of a grid-connected microgrid, which addresses power quality issues and ensures effective control through demand side management.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Cong Zeng, Ziyu Chen, Jizhong Zhu, Fellew Ieee
Summary: This paper introduces a distributed solution method for the multi-objective OPF problem, using a coevolutionary multi-objective evolutionary algorithm and the idea of decomposition. The problem is alleviated by decomposing decision variables and objective functions, and a new distributed fitness evaluation method is proposed. The experimental results demonstrate the effectiveness of the method and its excellence in large-scale systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)