Article
Automation & Control Systems
Pudong Ge, Boli Chen, Fei Teng
Summary: This article presents an event-triggered distributed model predictive control strategy for managing the voltage magnitude of distributed generators in a microgrid to achieve a balance between control performance and communication and computation burdens. Additionally, an adaptive nonasymptotic observer is used to estimate internal and output signals of generators, cooperating with the DMPC-based voltage regulator to optimize control performance.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Green & Sustainable Science & Technology
Salish Maharjan, Ashwin M. Khambadkone, Jimmy Chih-Hsien Peng
Summary: The paper proposes a control scheme for the high penetration of renewables in the distribution network, in which inverter-based Distributed Energy Resources respond locally and Robust Constrained Model Predictive Control ensures voltage stability. The Centralized Controller is implemented in Python for communication with the network model, and the performance is compared with Deterministic Model Predictive Control, showing significant advantages.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2021)
Article
Engineering, Electrical & Electronic
Zhuoli Zhao, Juntao Guo, Xi Luo, Chun Sing Lai, Ping Yang, Loi Lei Lai, Peng Li, Josep M. Guerrero, Mohammad Shahidehpour
Summary: This paper proposes a distributed robust model predictive control (DRMPC)-based energy management strategy for islanded multi-microgrids to address the issues caused by uncertain renewable energy output in microgrid systems. This strategy combines the advantages of robust optimization and model predictive control, and forms a dynamic energy trading market to enhance the overall economy of the multi-microgrid system.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Green & Sustainable Science & Technology
Amr Saleh, Hany M. Hasanien, Rania A. Turky, Balgynbek Turdybek, Mohammed Alharbi, Francisco Jurado, Walid A. Omran
Summary: Renewable energy sources (RES) have been increasingly integrated into power networks, especially in microgrids, leading to a significant decrease in system inertia. This reduction in inertia negatively impacts microgrid frequency stability, particularly in islanded operations. To address this issue, this study proposes a virtual inertia frequency control concept combined with optimal model predictive control (MPC) using the African Vultures Optimization Algorithm (AVOA). Simulation results demonstrate the effectiveness of the proposed AVOA-based MPC in improving microgrid frequency resilience and the role of battery energy storage (BES) units in enhancing transient responses.
Review
Multidisciplinary Sciences
Darioush Razmi, Oluleke Babayomi, Alireza Davari, Tohid Rahimi, Yuntao Miao, Zhenbin Zhang
Summary: This article reviews the application of model predictive control (MPC) in distributed energy resources (DER) in microgrids, with a focus on energy conversion in solar photovoltaic, wind, and energy storage systems, as well as increasing reliability of grid-connected converters under (a)symmetrical grid faults. The potential of MPC for stable multi-variable control performance of DERs is highlighted.
Article
Energy & Fuels
Zhengfa Zhang, Filipe Faria da Silva, Yifei Guo, Claus Leth Bak, Zhe Chen
Summary: This paper proposes a double-layer stochastic model predictive control algorithm to address the challenges posed by high penetration of renewable energy on voltage control. The algorithm achieves voltage regulation through coordination of upper layer and lower layer controllers, controlling voltage regulation devices and distributed generations in different timescales. Case studies show that the proposed algorithm outperforms traditional control methods and two-stage stochastic voltage control.
Review
Engineering, Electrical & Electronic
Swagat Kumar Panda, Bidyadhar Subudhi
Summary: Several challenges are faced when integrating microgrids with existing utility grids, such as low inertia, intermittent renewable energy resources, sensor and actuator faults, unbalanced and nonlinear loads, supply-demand mismatch, and uncertain switching functions of power electronic converters. Microgrid control relies heavily on communication networks, which are prone to various failures and cyber attacks. There is a lack of research on control schemes for microgrids in the literature. Hence, this paper provides a comprehensive review of robust and adaptive control schemes that address the challenges posed by communication constraints, uncertainties, and disturbances for different microgrid topologies. It concludes that robust and adaptive controllers offer improved performance compared to traditional controllers in terms of transient and steady-state behavior and robustness.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Automation & Control Systems
Eva Masero, Pablo R. Baldivieso-Monasterios, Jose M. Maestre, Paul A. Trodden
Summary: This article presents a distributed implementation of model predictive controller with information exchange for managing a distributed networked system of coupled dynamic subsystems. A coalitional control method is proposed, where local controllers coalesce into clusters to improve performance and solve plug-and-play problems. The main contribution is a tube-based coalitional approach that ensures recursive feasibility and stability in the face of plug-and-play operations. The simulation results demonstrate the benefits of the proposed control method.
Article
Thermodynamics
Feixiang Jiao, Yuan Zou, Xudong Zhang, Bin Zhang
Summary: This paper proposes a two-stage optimal framework for the online dispatch of a grid-connected DC microgrid, aiming to address the uncertainties of renewable energy and load demand. The framework includes a power coordination model and a charging station allocation model, and its superiority is validated through numerical case studies.
Article
Engineering, Electrical & Electronic
Fan Yang, Shibing Yu, Jian Zhao, Dongdong Li, Shunfu Lin
Summary: In this paper, a distributed reconfiguration model predictive control (DRMPC) based frequency control of microgrid clusters considering dynamic topology is presented. The DRMPC controller is designed to minimize the frequency deviation while considering the output power constraint of each distributed generation. The proposed control strategy is verified by a cluster of five sub-microgrids connected via tie lines.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Energy & Fuels
Fujun Bao, Jianbo Guo, Weisheng Wang, Guanghui Li, Bin Wang
Summary: This paper investigates the use of Virtual Synchronous Generator (VSG) technology to address oscillation issues in microgrids. It proposes a cooperative control method for multiple VSGs to improve output control and reduce power imbalances and frequency differences, resulting in significant mitigation of oscillations and improved dynamic characteristics of the microgrid.
Article
Energy & Fuels
Noushin Poursafar, M. J. Hossain, Seyedfoad Taghizadeh
Summary: This paper presents an enhanced distributed DC-bus signaling control strategy for converters of photovoltaic systems (PVs) to make the islanded DCMG less dependent on the backup energy storage system (BESS). The proposed control method maintains DC-bus voltage via intelligently managing output powers of the PVs and switches between MPPT and voltage regulating control operations. It effectively protects the DCMG from shutdowns during the absence of the BESS and reduces oscillations on the DC-bus voltage during the presence of the BESS.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
Article
Automation & Control Systems
Eva Masero, J. M. Maestre, Antonio Ferramosca, Mario Francisco, Eduardo F. Camacho
Summary: This article introduces a novel clustering model predictive control technique that plans transitions to the best cooperation topology over a prediction horizon. The addition of a transition horizon variable in the optimization problem allows for calculating the optimal instant for introducing the next topology. Recursive feasibility and robust stability conditions for the system are also provided. The proposed control method is tested on a simulated eight-coupled tanks plant.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2021)
Article
Chemistry, Multidisciplinary
Wei Jin, Shuo Zhang, Jian Li
Summary: The development of active distribution networks (ADN) with a high proportion of renewable energy, driven by the energy crisis and environmental concerns, poses challenges to power system operation. Network reconfiguration is used in the planning stage to enhance the adjustable capacity of the power system and promote the consumption of renewable energy. A robust optimization model considering network reconstruction and distributed power generation in ADN is proposed, incorporating a wind-light-load uncertain scenario set to address uncertainty. The influence of network reconfiguration on DG planning, economy, and reliability of ADN is analyzed through simulation, validating the model.
APPLIED SCIENCES-BASEL
(2023)
Review
Energy & Fuels
Swetalina Sarangi, Binod Kumar Sahu, Pravat Kumar Rout
Summary: This paper highlights the importance and challenges of protection in DC microgrids, as well as some loopholes in current research. By systematically and chronologically reviewing DC microgrid systems, some reliable improvements have been suggested.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Yongji Cao, Qiuwei Wu, Hengxu Zhang, Changgang Li
Summary: This paper proposes a multi-objective optimal siting and sizing scheme for battery energy storage system (BESS) in power systems, to mitigate frequent and severe active power disturbances. The scheme adjusts output power flexibly to improve frequency stability and power flow distribution. The optimization model considers transient frequency regulation capability (TFRC), line capacity, life cycle cost, and generation cost. By using linear weighted method, big-M method, and multi-cut generalized Benders decomposition, the intractable optimization model is transformed into subproblems and a master problem iteratively solved to determine the location and capacity of the BESS. The proposed scheme shows superior performance in improving frequency nadir and alleviating post-disturbance line overload.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Siyuan Guo, Bin Zhou, Yun Yang, Qiuwei Wu, Yue Xiang, Yang He
Summary: This article proposes an adaptive acoustic spectrum analysis method with refined composite multiscale dispersion entropy to extract informative fault-related time-frequency vocal features for facilitating fault diagnosis of direct-buried transformer substations (DBTS). A time-series generative adversarial network based fault data augmentation model is presented to enrich the training dataset while preserving temporal dynamics of the original fault data. Furthermore, a multi-source ensemble learning strategy is developed to integrate heterogeneous sub-classifiers based on the dynamic weighted fusion of electrical monitoring data and acoustic signals to improve fault diagnosis accuracy of DBTS.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Mingqiang Wang, Ming Yang, Zhen Fang, Mengxia Wang, Qiuwei Wu
Summary: There is a significant gap between academic research and practical application in power distribution system planning (PDSP). Existing PDSP models in academic research mainly focus on cost as the objective function and have constraints such as power flow equality, voltage limits, and capacity limits. However, these models are rarely used in real distribution system companies. This paper proposes a new feeder planning model for urban distribution networks, considering practical requirements such as load moment, block loads, street layout, network configuration, and the crossing requirement of feeders. The model is solved using mixed integer linear programming and is demonstrated on test and real distribution systems.
IEEE TRANSACTIONS ON POWER SYSTEMS
(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
Xiaodong Yang, Zhiyan Zhou, Youbing Zhang, Jiancun Liu, Jinyu Wen, Qiuwei Wu, Shijie Cheng
Summary: This paper proposes a co-deployment framework for soft open points (SOPs) and remote-controlled switches (RCSs) to improve the resilience and management of flexible resources in distribution networks. The model optimizes the investment cost of SOPs and RCSs, as well as the cost caused by de-energized loads, while considering operational constraints. It also analyzes the tradeoff between resilience and cost.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Xiaodong Yang, Chongbo Xu, Jinyu Wen, Youbing Zhang, Qiuwei Wu, Wenping Zuo, Shijie Cheng
Summary: This paper proposes a multi-period cooperative solution for the jointly repair and restoration problem in distribution systems (DSs) to minimize the de-energized loads. A novel fully-controlled power-electronic device SOP (soft open point) and fault isolation are included in the proposed scheme to accelerate system restoration. A new virtual power flow based automatic solution is presented to adaptively perform control mode switching for the SOPs in faulted DS. A co-optimization model is formulated that coordinates SOP control, repair scheduling, and DS restoration to enhance system resilience. Fault isolation is also conducted to guarantee the safety of repair crews.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Electrical & Electronic
Sheng Cai, Yunyun Xie, Qiuwei Wu, Xiaolong Jin, Menglin Zhang, Zhengrong Xiang
Summary: This paper proposes a fast and reliable sequential service restoration (SSR) methodology to enhance the resilience of the distribution system (DS) after an outage. The methodology dispatches mobile emergency generators (MEGs) as backup sources to form microgrids (MGs) and sequentially restore out-of-service loads. It includes a two-stage dispatching model that considers preventive control stage (PCS) and emergency control stage (ECS), and optimizes SSR decisions based on stage-based uncertainties.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Wenshu Jiao, Qiuwei Wu, Sheng Huang, Jian Chen, Canbing Li, Bin Zhou
Summary: This paper presents a distributed voltage control scheme for unbalanced distribution networks with single-/three-phase distributed generations based on distributed model predictive control. The scheme optimally coordinates the power outputs of DG units to regulate threephase voltages and mitigate voltage fluctuations. Two control modes, preventive and corrective, are designed based on the operation conditions of the networks.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Qingtao Li, Jianxue Wang, Yao Zhang, Qiuwei Wu, Chenjia Gu, Qian Yang
Summary: This paper proposes a three-level coordinated planning scheme for wind-storage hybrid power plants (WSHPP) and transmission networks, along with an algorithm to solve the problem. Numerical experiments show the effectiveness of the proposed planning scheme and the feasibility of the solution algorithm.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Yufan Zhang, Honglin Wen, Qiuwei Wu, Qian Ai
Summary: Prediction intervals (PIs) are effective tool for quantifying uncertainty in distribution systems. Traditional central PIs are not suitable for skewed distributions and their offline training is vulnerable to unforeseen changes. We propose an optimal online estimation approach that adapts to different data distributions by adaptively determining probability proportion pairs for quantiles. The approach uses reinforcement learning to integrate adaptive selection and quantile predictions, improving PIs' quality. Case studies show that the proposed method outperforms traditional methods in adapting to data distribution and is more robust against concept drift.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Electrical & Electronic
Jin Tan, Qiuwei Wu, Xuan Zhang
Summary: This paper proposes a novel three-stage planning model for integrated electricity and heat systems that consider seasonal thermal energy storage and short-term TES. The model addresses multiscale uncertainties by decomposing heat demand, separating the operation of STES and short-term TES, and utilizing fuzzy sets and scenarios. A new STES model is developed to improve computational efficiency, and a pairwise reformulation is used to linearize bilinear terms. Numerical results demonstrate the effectiveness of the proposed model in improving cost efficiency and reducing wind power curtailments.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Electrical & Electronic
Chuanhao Hu, Xuan Zhang, Qiuwei Wu
Summary: This paper proposes a novel coordinated active and reactive control strategy for DERs, using a distributed event-triggered heavy ball method, allowing DERs to offer voltage regulation and frequency support in a unified framework. The proposed control strategy effectively saves communication cost and accelerates the convergence rate.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Green & Sustainable Science & Technology
Xiaodong Yang, Zehao Song, Jinyu Wen, Lijian Ding, Menglin Zhang, Qiuwei Wu, Shijie Cheng
Summary: This paper proposes a novel network-constrained transactive control (NTC) framework that addresses both economic and secure issues for a multi-microgrids-based distribution network considering uncertainties. The framework integrates a transactive energy market with a power-electronics device (soft open point) based AC power flow regulation technique to improve economic benefits and ensure voltage security. The original bilevel game problems are transformed into a single-level mixed-integer second-order cone programming problem to improve solving efficiency.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Engineering, Electrical & Electronic
Xinyue Chang, Yinliang Xu, Hongbin Sun, Qiuwei Wu
Summary: The increasing number of prosumers with various distributed energy resources promotes energy transactions in active distribution networks for lower cost, more flexibility, lower carbon footprints, and higher reliability. A privacy-preserving distributed energy transaction approach is proposed to minimize the overall objective of renewable energy generation curtailment penalty and operational cost while satisfying power flows and voltage magnitude constraints. The proposed approach encrypts private information by adding a noise term and a secret function to the information exchange process.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Energy & Fuels
Jia Liu, Pingliang Zeng, Hao Xing, Yalou Li, Qiuwei Wu
Summary: This paper presents a stochastic optimal operation problem of gas turbine integrated distribution networks in the presence of active management schemes, which is formulated as a multi-objective chance-constrained mixed integer nonlinear programming problem. The collaboration of normal boundary intersection and the dynamic niche differential evolution algorithm is proposed to handle the optimal operation mode. The simulation results demonstrate the effectiveness of the proposed model.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2023)
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)
