Article
Thermodynamics
Wenyi Du, Juan Ma, Wanjun Yin
Summary: This paper firstly uses Monte Carlo simulation to study the disorderly charging behavior of electric vehicles (EVs), and presents an improved particle swarm optimization (PSO) algorithm to model the orderly charging strategy. By adjusting the inertia weight index and learning factor, the problems of poor local optimization ability and premature convergence of the original PSO are alleviated. Experimental results demonstrate that the proposed orderly charging strategy can significantly reduce charging costs and peak-valley differences.
Article
Thermodynamics
Tao Yi, Xiaobin Cheng, Peng Peng
Summary: This paper proposes a two-stage model for optimizing charging scheduling and charging station construction planning, which uses Monte Carlo simulation and particle swarm optimization algorithm to reduce the social comprehensive cost.
Article
Thermodynamics
Ning Wang, Hangqi Tian, Huahua Wu, Qiaoqian Liu, Jie Luan, Yuan Li
Summary: This study proposed a multi-stage optimization strategy to optimize the location and capacity of electric vehicle charging stations for the Robotaxi fleet. The strategy included fleet sizing, charging demand simulation, model construction, and solution. The effectiveness of the proposed model and algorithm was analyzed using real data from Chengdu, China.
Article
Engineering, Marine
Jungwon Huh, Achintya Haldar, Nhu Son Doan, Phu Van Dang, Van Ha Mac
Summary: This study proposes a new method to simplify computational burdens in Monte Carlo simulation, conducting reliability analysis and optimization in aspects like slopes and foundation stability, validating its effectiveness.
Article
Energy & Fuels
Surasit Sangob, Somporn Sirisumrannukul
Summary: This paper investigates the impact of electric vehicles on distribution systems and how to optimize charging behaviors through algorithms to reduce costs and improve performance; experimental results show that sequential optimization can help improve customer voltage profiles and save energy losses.
FRONTIERS IN ENERGY RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Bulent Alptekin, Sukru Acitas, Birdal Senoglu, Cagdas Hakan Aladag
Summary: Determining the parameters of metaheuristic methods, such as particle swarm optimization, is crucial. Statistical analysis can help identify the most important parameters, reducing the dimension of the parameter search space.
Article
Thermodynamics
Abhishek Sit, Rhena Wulf, Tobias Fieback, Prabal Talukdar
Summary: An inverse radiation analysis is conducted to identify the spectral radiative properties of highly porous closed cell polymeric foams using the coupled Monte Carlo-Particle Swarm Optimization method. The thermal radiation within the foam is simulated using an Open Message Passing Interface (MPI) based parallel Monte Carlo method. The Particle Swarm Optimization (PSO) with adaptive weighted delay velocity is used to inversely identify the spectrally dependent transport extinction coefficient and scattering albedo of foams.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2023)
Article
Engineering, Multidisciplinary
Hamdy A. El-Ghandour, Samer M. Elabd, Emad Elbeltagi
Summary: This paper presents a methodology for optimal design or rehabilitation of water distribution systems under steady-state and transient conditions, considering uncertainty in pipe roughness coefficients. The study uses particle swarm optimization and Monte Carlo simulation to analyze the hydraulic availability indices and system reliabilities. Results show a decrease in system reliability with increasing pipe roughness uncertainty.
AIN SHAMS ENGINEERING JOURNAL
(2021)
Article
Operations Research & Management Science
Calogero Orlando, Angela Ricciardello
Summary: The paper introduces a continuous formulation of the PSO problem, analyzes its convergence and compares it with the standard PSO, incorporates the stochastic nature of PSO through Monte Carlo analysis. Comparisons with other optimization methods show a success rate greater than 93%.
OPTIMIZATION LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Felipe L. Miranda, Leonardo W. Oliveira, Edimar J. Oliveira, Erivelton G. Nepomuceno, Bruno H. Dias
Summary: This paper presents an algorithm, called non-dominated Monte Carlo simulation (ND-MCS), to solve the multi-objective transmission expansion planning (TEP) problem including the investment and reliability criteria. The algorithm considers reliability using the Expected energy not supplied (EENS) index, and integrates a Support Vector Machine (SVM) network. The proposed approach is tested in three systems, including a practical Brazilian network.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Civil
Kang Gao, Duy Minh Do, Sheng Chu, Gang Wu, H. Alicia Kim, Carol A. Featherston
Summary: This study presents a novel computational framework for Robust Topology Optimization (RTO) considering imprecise random field parameters. The proposed method provides upper and lower bounds for mean and standard deviation of compliance, and obtains optimized topological layouts for different scenarios. The validity and accuracy of the method are rigorously examined by comparing with other optimization methods.
THIN-WALLED STRUCTURES
(2022)
Article
Mechanics
Himanshu Sharma, Ranjan Ganguli
Summary: This paper investigates the reliable and robust optimum design of a higher-order sandwich composite beam under the effect of uncertainty in material properties. Various optimization approaches and surrogate models were used to enhance the efficiency of the process, and the numerical results showed significant improvement in the optimal design considering uncertainty.
COMPOSITE STRUCTURES
(2021)
Article
Computer Science, Artificial Intelligence
Manh Duong Phung, Quang Phuc Ha
Summary: This paper introduces a new algorithm named SPSO for UAV path planning, and demonstrates its superiority over other optimization algorithms in various scenarios through comparative experiments.
APPLIED SOFT COMPUTING
(2021)
Article
Acoustics
Yihong Gu, Yucheng Liu, Congda Lu
Summary: In this study, the effects of working parameters on brake noise were analyzed using dynamometer test data and the finite element method (FEM). A method to reduce brake noise was developed, which involved Monte Carlo sampling for variations in brake lining parameters and particle swarm optimization for calculating the optimal parameter combination. A dynamometer test was conducted to validate the effectiveness of optimization in mitigating brake noise.
SHOCK AND VIBRATION
(2021)
Article
Energy & Fuels
Yuana Adianto, Craig Baguley, Udaya Madawala, Nanang Hariyanto, Suwarno Suwarno, Teguh Kurniawan
Summary: A novel charge scheduling strategy is proposed in this paper to address the needs of vertically structured power systems without relying on time-of-use pricing. By providing a decision-making framework that considers the considerations of transmission and distribution network operators and allowing for dynamically changing charging loads through timely forecast updates, the strategy demonstrates its effectiveness in a case study.
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)
