Article
Computer Science, Information Systems
Chinwe Peace Igiri, Deepshikha Bhargava, Theodora Ekwomadu, Funmilayo Kasali, Bassey Isong
Summary: Real-world optimization problems often require advanced algorithms. This study focuses on the petroleum product scheduling problem, which is a complex optimization task in the combinatorial problem category. The researchers leveraged bio-inspired approaches, specifically the Ant Lion Optimizer (ALO) and Chaotic Particle Swarm Optimization (CPSO), to improve the solution quality. The results showed significant reductions in cost and high constraint satisfaction rates. Further research on constraint handling methods and other bio-inspired computation approaches is recommended.
Article
Thermodynamics
Shoubin Wang, Jie Song, Guili Peng, Yunlong Li, Yuan Zhou
Summary: This paper studies the inverse heat transfer problem in a two-dimensional cross-section of a horizontal pipe and proposes an inversion algorithm based on the ALO-SSA algorithm to estimate the unknown fluid temperature close to the inner wall of the pipe. The algorithm exhibits lower average error in temperature estimation at 0 degrees and 30 degrees, and shows good speed and accuracy for solving similar problems.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2023)
Article
Computer Science, Information Systems
Juginder Pal Singh, Manoj Kumar
Summary: Crowd scene research has become the most active and trendy topic in computer vision applications. Panic behavior is a key indication of abnormal behavior in human crowds, and detecting it helps prevent disastrous situations. Existing methods for detecting panic behavior in crowded scenes often suffer from performance degradation due to varying object density. To address this, a Chronological-Ant Lion Optimizer-based Deep Convolutional Neural Network (Chronological ALO-based Deep CNN) is proposed. The Chronological ALO is used to train the Deep CNN classifier for better detection results. The proposed method achieved superior performance with accuracy, sensitivity, and specificity values of 95.833%, 96.296%, and 96.329%, respectively.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Sunita Kumawat, Chanchal Dudeja, Pawan Kumar
Summary: This paper presents a technique that uses the Fuzzy based Pareto Optimal approach to discover the shortest paths in a network graph. The method finds the shortest paths using a set of rules and selects the optimal shortest path using the Ant Lion Optimization algorithm. Experimental results demonstrate the superiority of this method in performance compared to other approaches.
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Information Systems
Indah Soesanti, Ramadoni Syahputra
Summary: Multiobjective ant lion optimization (MALO) is a technique that imitates ant foraging behavior and has many advantages. This study proposes a MALO-based multiobjective optimization technique to determine the optimal location and capacity of distributed energy resources (DERs), and the results show that MALO can improve distribution network performance.
Article
Computer Science, Interdisciplinary Applications
N. Eslami, S. Yazdani, M. Mirzaei, E. Hadavandi
Summary: The paper introduces a novel population-based optimization paradigm called Aphid-Ant Mutualism (AAM) inspired by the mutual relationship between aphids and ants, which effectively avoids premature convergence and converges to the global optimum. The AAM algorithm shows promising and competitive outcomes with more accurate solutions and faster convergence rates compared to other meta-heuristic algorithms.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Review
Computer Science, Interdisciplinary Applications
Laith Abualigah, Mohammad Shehab, Mohammad Alshinwan, Seyedali Mirjalili, Mohamed Abd Elaziz
Summary: The Ant Lion Optimizer (ALO) is a novel metaheuristic swarm-based approach introduced by Mirjalili in 2015 to emulate the hunting behavior of ant lions in nature. It aims to enhance the performance of functional and efficient during the optimization process by finding the minimum or maximum values to solve a certain problem. Metaheuristic algorithms have become a research focus with the introduction of decision-making and asses the benefits in solving various optimization problems.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
D. Santhakumar, S. Logeswari
Summary: The classification of cancers using Microarray data analysis is crucial, and Evolutionary Algorithms show advantages over conventional individual search methods. Ant Colony Optimization and Ant Lion Optimization algorithms, inspired by nature, are widely used for their efficiency in various optimization tasks.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Rama Rani, Ritu Garg
Summary: The rapid growth of cloud data centers has led to significant energy consumption concerns for cloud service providers. The increasing demand for scientific workflow applications poses challenges for efficient workflow scheduling. The PBMO-DALO algorithm addresses the conflicting objectives of minimizing makespan and energy consumption in cloud data centers, outperforming other competing algorithms with better trade-off solutions.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Sanchari Deb, Xiao-Zhi Gao
Summary: Transportation electrification is seen as a viable solution to global warming, air pollution, and energy crisis, but the optimal placement of charging infrastructure for Electric Vehicles presents a complex problem involving multiple design variables, objective functions, and constraints.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Changting Zhong, Gang Li, Zeng Meng
Summary: This paper presents a novel swarm-based metaheuristic algorithm called beluga whale optimization (BWO), which is inspired by the behaviors of beluga whales, for solving optimization problems. BWO consists of three phases: exploration, exploitation, and whale fall, corresponding to pair swim, prey, and whale fall behaviors, respectively. The self-adaptive balance factor and probability of whale fall in BWO play significant roles in controlling the exploration and exploitation capabilities. Additionally, Levy flight is introduced to enhance the global convergence in the exploitation phase. The effectiveness of BWO is evaluated using 30 benchmark functions and compared with 15 other metaheuristic algorithms through qualitative, quantitative, and scalability analysis. The results show that BWO is a competitive algorithm for solving unimodal and multimodal optimization problems. Furthermore, BWO achieves the first overall rank in the scalability analysis of benchmark functions among the compared metaheuristic algorithms. Four engineering problems are also solved to demonstrate the merits and potential of BWO in solving complex real-world optimization problems. The source code of BWO is publicly available.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Ying Li, Yindi Yao, Shanshan Hu, Qin Wen, Feng Zhao
Summary: To improve the quality of service and prolong the network lifetime of wireless sensor networks (WSNs), this article proposes an improved MOALO algorithm based on fast nondominated sorting (NSIMOALO). The algorithm utilizes fast nondominated sorting and elite strategy to avoid local optimal solutions, and introduces Levy flight to enhance global optimization ability. Simulation results show that NSIMOALO algorithm achieves higher convergence and coverage compared to other algorithms. When applied to WSNs sensor node deployment, it increases the coverage rate by 12.753%, 12.413%, and 4.492% and decreases sensor nodes average moving distance by 2.551, 2.316, and 4.457 m compared to MOALO algorithm, NSGA-II algorithm, and NSMOFPA algorithm, respectively.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Multidisciplinary
Shivi Kesarwani, Rajesh Kumar Verma
Summary: This article introduces a hybrid methodology of Grey theory and the Ant Lion Optimizer algorithm, and examines the impact of varying constraints on the cutting process through Taguchi experimental design, with validation test confirming its effectiveness.
Article
Computer Science, Interdisciplinary Applications
Amol M. Dalavi, Alyssa Gomes, Aaliya Javed Husain
Summary: This paper statistically evaluates the impact and importance of nature-inspired optimization by analyzing works published between 2016 and 2020. The study finds that China, India, and the US are the highest contributors, and computer science, engineering, and mathematics are the top disciplines contributing to research. The top application areas include optimization, artificial intelligence, and decision sciences.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Hardware & Architecture
K. SureshKumar, P. Vimala
Summary: In this study, an energy-efficient and trust-based routing model is proposed using the E-ALWO algorithm, which selects cluster heads based on energy and delay constraints.
Article
Computer Science, Artificial Intelligence
Astha Chawla, Prakhar Agrawal, Bijaya Ketan Panigrahi, Kolin Paul
Summary: This paper presents a novel cyber-attack resilient framework for the smart-grid system, incorporating attack detection and mitigation modules. The proposed model successfully detects anomalies in real-time and reconstructs the compromised data, ensuring the system's resilience.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Pushpa Kumari, Nishant Kumar, Bijaya Ketan Panigrahi
Summary: In this paper, a novel Parabolic Curve-fitting based Hill Climbing (PCHC) MPPT algorithm is proposed for maximum power extraction from solar photovoltaic panels. The algorithm is integrated with a reduced sensor-based approach, making it cost-effective for residential use. The proposed methodology utilizes the parabolic nature of the PV characteristic near the Maximum Power Point (MPP) to quickly detect and calculate the optimum power voltage. By reducing perturbation size and taking different step sizes for irradiation level changes, the algorithm overcomes oscillation and improves dynamic performance near the MPP. Validation experiments on different irradiation patterns confirm the effectiveness of the proposed algorithm.
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
(2023)
Article
Thermodynamics
Poonam Singh, Manjaree Pandit, Laxmi Srivastava
Summary: In this study, an optimal sizing model is developed for a hybrid micro-grid system (HMGS) that includes solar photovoltaic, wind turbine, diesel generator, and battery. A tri-objective formulation considering techno-socio-economic factors is proposed to find the optimal size and configuration. Dynamic domain search employing a hybrid intelligent computational technique is used to improve the search efficiency. The best solution is identified using a fuzzy attainment module. The optimal sizing is analyzed considering the effect of selected optimization objectives, and multiple choices are offered to the designer based on preferences. The results show that a system with solar PV capacity of 78.44 kW, wind turbine of 95 kW, and a battery of 2 kW is the best option.
Article
Engineering, Electrical & Electronic
Arjita Pal, Diptak Pal, Bijaya Ketan Panigrahi
Summary: This paper proposes a new current saturation strategy (CSS) for grid-forming (GFM) inverters to comply with low-voltage ride-through (LVRT) capability requirements. The proposed control philosophy limits the output current during LVRT using a new control parameter, the power factor angle (PFA), enabling the GFM inverters to adhere to standardized grid codes. A nonlinear mathematical model capturing the dynamics of a GFM inverter with current limiting control is developed, and a simplified equivalent circuit model is used to analytically evaluate the proposed CSS. Numerical and experimental results validate the accuracy of the CSS in assessing the large-signal stability of a GFM inverter under severe symmetrical grid faults.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Parul Arora, Seyed Mohammad Jafar Jalali, Sajad Ahmadian, B. K. Panigrahi, P. N. Suganthan, Abbas Khosravi
Summary: Wind power forecasting is crucial for power system planning and scheduling. Optimizing the hyperparameters of deep neural networks (DNNs) using evolutionary algorithms is an effective approach. In this article, a novel evolutionary algorithm based on the grasshopper optimization algorithm is proposed to optimize the hyperparameters of a wind power forecasting model. The proposed model outperforms benchmark DNNs and other neuroevolutionary models in terms of learning speed and prediction accuracy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Geeta Pathak, Bhim Singh, B. K. Panigrahi
Summary: This paper investigates a three-phase wind-solar-photovoltaic microgrid system that can operate in grid-tied and island modes under steady state and in DSTATCOM mode, utility-interactive mode and disconnecting mode under dynamic state. The microgrid uses a single Voltage Source Inverter (VSI) with reduced power converters and switches. A battery bank is utilized at the DC bus of the VSI for load leveling and power balance control. The VSI's control also improves Power Quality (PQ) and provides power backup during abnormal grid conditions.
IETE JOURNAL OF RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Kirti Gupta, Subham Sahoo, Rabindra Mohanty, Bijaya Ketan Panigrahi, Frede Blaabjerg
Summary: This article presents a novel noninvasive anomaly diagnosis mechanism for inverter-based resources (IBRs) in large power systems. It can accurately classify anomalies within 5 ms using locally measured voltage and frequency as inputs. The proposed mechanism provides the fastest decision compared to existing techniques and has been validated on various systems.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Nishant Kumar, Bhim Singh, Bijaya Ketan Panigrahi
Summary: This paper presents a new voltage sensorless based model predictive control scheme for maximum power harvesting from a photovoltaic array for solar-powered EV charging. The control technique utilizes the first model predictive control with a PV array to predict the system state and eliminate the need for a voltage sensor. An adaptive concept is used for determining the operating point, improving tracking and dynamic performance. The control technique is verified on a PV system prototype under different shading and irradiance conditions, and the system stability is analyzed through the Bode plot.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Engineering, Electrical & Electronic
Muhammad Zarkab Farooqi, Bhim Singh, Bijaya Ketan Panigrahi
Summary: This article presents a voltage sensorless modulated model predictive control (VS-MMPC) approach for decoupling operation in electric vehicle (EV) chargers. The proposed approach reconstructs the dynamic model based on Euler's approximation to achieve decoupling voltage senseless operation. Comparative study and stability analysis demonstrate the improved dynamic performance and reduced execution time of the presented control.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Engineering, Marine
Karan Sareen, Bijaya Ketan Panigrahi, Tushar Shikhola, Rita Nagdeve
Summary: The ocean is a potential and limitless source of renewable energy, but the intermittent and irregular characteristic of wave energy is concerning for the stability of the power system. Accurate and trustworthy forecasts of ocean wave height have gained increased attention recently, as it is a crucial parameter for harnessing energy from ocean waves. In this study, a framework combining the CEEMDAN data decomposition algorithm and BiDLSTM deep learning algorithm is proposed to accurately forecast ocean significant wave height and wave energy. The empirical outcomes show that the proposed method is highly accurate compared to recently established forecasting algorithms in literature.
Proceedings Paper
Green & Sustainable Science & Technology
Purusharth Semwal, Vivek Narayanan, Bhim Singh, B. K. Panigrahi
Summary: To reduce water pollution, integrating non-conventional energy sources into the marine sector is an effective solution. This paper evaluates the performance of an emission-free marine microgrid under different operational conditions. Using the MATLAB-Simulink platform, an emission-free ferry is developed with a battery energy storage, solar photovoltaic system, propulsion motors, and service loads, and operated in various sea conditions. By employing a power management system and Black Widow Optimization, stability and regulation of the power system are ensured. The dual second-order generalized integrator and modified quasi type1 phase-locked loop are used for cold ironing mode to synchronize the ferry with the shore power system and provide distortion-free current.
2023 IEEE IAS GLOBAL CONFERENCE ON RENEWABLE ENERGY AND HYDROGEN TECHNOLOGIES, GLOBCONHT
(2023)
Proceedings Paper
Green & Sustainable Science & Technology
Sunaina Singh, Vivek Narayanan, Bhim Singh, B. K. Panigrahi
Summary: The paper presents a standalone system based on solar photovoltaic (PV)-ES energy storage. A battery is used as the energy storage (ES) due to the intermittent nature of solar energy. A bidirectional converter (BDC) is connected with the battery to regulate the DC-link voltage. The system's performance under steady-state and dynamic conditions is validated through simulations in MATLAB/Simulink.
2023 IEEE IAS GLOBAL CONFERENCE ON RENEWABLE ENERGY AND HYDROGEN TECHNOLOGIES, GLOBCONHT
(2023)
Article
Engineering, Electrical & Electronic
Chandra Bhushan Kumar, Arnab Kumar Mondal, Manvir Bhatia, Bijaya Ketan Panigrahi, Tapan Kumar Gandhi
Summary: Sleep apnea is a common sleep disorder that can have serious health consequences. Polysomnography is an effective method for diagnosis, but it is time-consuming. This study proposes a self-supervised learning approach using ECG signals for detecting sleep apnea.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Diptak Pal, Bijaya Ketan Panigrahi
Summary: This article presents a generalized reduced-order modeling approach for assessing the transient synchronization stability of multiple grid-tied converter systems with heterogeneous characteristics. The approach uses the nonlinear quasi-static dynamics of the phase-locked loop (PLL) to obtain the reduced-order models (ROM) of heterogeneous grid-feeding converters. A novel methodology based on Lyapunov's direct method is proposed for analyzing the transient synchronization stability. Numerical simulations demonstrate the accuracy and computational efficiency of the ROM, and verify the efficacy of the proposed methodology for heterogeneous grid-feeding multi-converter systems.
IEEE TRANSACTIONS ON POWER DELIVERY
(2023)
Article
Energy & Fuels
Subarni Pradhan, Bhim Singh, Bijaya Ketan Panigrahi
Summary: This study proposes a grid interactive solar PV system with low voltage ride through capability. The system ensures continuous power supply to the loads and the grid even when the supply voltage drops by more than 10%. A current limiting logic is incorporated to prevent the grid fed inverter current from exceeding the safe limit. The study also introduces a frequency adaptive higher order complex filter for estimating the positive and negative sequence voltages from unbalanced supply voltages.
IET ENERGY SYSTEMS INTEGRATION
(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)
