Records with Subject: Energy Management
Showing records 1 to 25 of 1388. [First] Page: 1 2 3 4 5 Last
An Improved Dual Second-Order Generalized Integrator Phased-Locked Loop Strategy for an Inverter of Flexible High-Voltage Direct Current Transmission Systems under Nonideal Grid Conditions
Lai Peng, Zhichao Fu, Tao Xiao, Yang Qian, Wei Zhao, Cheng Zhang
January 12, 2024 (v1)
Keywords: DC bias, flexible DC transmission, harmonic voltage, PLL, power quality, unbalance voltage
High-voltage flexible power systems, with their intrinsic characteristics, play an increasingly important role in electronic power systems. Synchronization between the inverter and the grid needs to be achieved by a phase-locked loop (PLL), the performance of which determines the quality of power transmission. This paper proposes a PLL adapted to extremely harsh grid conditions. Firstly, the traditional synchronous reference frame PLL and the dual second-order generalized integrator (DSOGI-PLL) are analyzed, and the errors in phase-locking and the shortcomings of these two methods in the presence of DC components in the grid are pointed out. Secondly, based on the harmonic grid voltage, a repetitive control internal model is introduced by DSOGI to realize the real-time tracking and regulation of the harmonic signals in order to suppress the harmonic voltage disturbance. In addition, a DC bias elimination and frequency adaptive method is proposed to solve the problems of DC bias and gri... [more]
Frequency and Inertial Response Analysis of Loads in The Chilean Power System
Juan Quiroz, Roberto Perez, Héctor Chávez, Carlos Fuentes, Matías Díaz, José Rodriguez
January 12, 2024 (v1)
Keywords: frequency measurement, frequency response, inertia, power systems, smart grids
The integration of power electronics-interconnected generation systems to the grid has fostered a significant number of concerns on power system operations, particularly on the displacement of synchronous generators that leads to a reduction in the grid’s overall inertia and frequency response. These concerns have raised a significant amount of state-of-the-art mathematical proposals on how to estimate system inertia; however, the majority of the proposals do not differentiate generator inertia from load inertia. When inertia prediction for control room applications is required in real-time, the current state-of-the-art proposals use the inertia of generators as a proxy for a minimum, overall inertia estimate, counting the number of units committed in real-time and adding up their inertia. However, as dynamic conditions are becoming challenging with the integration of power electronics-interconnected generation systems, it is important to quantify the amount of inertia from the loads,... [more]
Fault Detection and Location of 35 kV Single-Ended Radial Distribution Network Based on Traveling Wave Detection Method
Xiaowei Xu, Fangrong Zhou, Yongjie Nie, Wenhua Xu, Ke Wang, Jian OuYang, Kaihong Zhou, Shan Chen, Yiming Han
January 5, 2024 (v1)
Keywords: 35 kV, distribution network, Fault Detection, traveling wave method, wavelet conversion method
With the progress of society and the iterative improvement of infrastructure construction, the power grid transmission lines have also entered an era of intelligence. The national distribution system has made ensuring the regular operation of the distribution network as well as prompting troubleshooting and detection its top priority. Research on fault diagnosis for 35 kV single-ended radial distribution networks is still in its infancy compared to other hot topics in the industry, such as short-circuit fault detection and fault node localization. This study adopts the 35 kV single-ended radial distribution network as a model, detects fault lines via the traveling wave method, and accurately locates fault nodes using the wavelet conversion method, hoping to quickly identify and locate fault nodes in distribution networks. The experimental results demonstrate that the research method can quickly identify the faulty line and carry out further fault node location detection. The final obta... [more]
New Technology and Method for Monitoring the Status of Power Systems to Improve Power Quality—A Case Study
Rahim Ildarabadi, Mahmoud Zadehbagheri
January 5, 2024 (v1)
Keywords: data compression, Fourier transform, harmonics, monitoring, power quality, steady-state analysis, transient analysis, wavelet transforms (WTs)
The identification and analysis of harmonics, frequency, and transient events are essential today. It is necessary to have available data relating to harmonics, frequency, and transient events to understand power systems and their proper control and analysis. Power quality monitoring is the first step in identifying power quality disturbances and reducing them and, as a result, improving the performance of the power system. In this paper, while presenting different methods for measuring these quantities, we have made some corrections to them. These reforms have been obtained through the analysis of power network signals. Finally, we introduce a new monitoring system capable of measuring harmonics, frequency, and transient events in the network. In addition, these values are provided for online and offline calculations of harmonics, frequency, and transient events. In this paper, two new and practical methods of the “algebraic method” are used to calculate network harmonics and wavelet... [more]
Capacity Management in Smart Grids Using Greedy Randomized Adaptive Search Procedure and Tabu Search
Hugo de Oliveira Motta Serrano, Cleberton Reiz, Jonatas Boas Leite
January 5, 2024 (v1)
Keywords: capacity management, distributed generator, distribution network, GRASP, load shedding, Tabu Search
Over time, distribution systems have progressed from small-scale systems to complex networks, requiring modernization to adapt to these increasing levels of active loads and devices. It is essential to manage the capacity of distribution networks to support all these new technologies. This work, therefore, presents a method for evaluating the impact of optimal allocation and sizing of DGs and load shedding for response demand programs on distribution networks to improve the reliability and financial performance of electric power systems. The proposed optimization tool uses the Greedy Randomized Adaptive Search Procedure and Tabu Search algorithms. The combined optimization of DG allocation simultaneously with load shedding, reliability indices, load transference, and the possibility of islanded operation significantly improves the quality of the planning proposals obtained by the developed method. The results demonstrate the efficiency and robustness of the proposed method, improving t... [more]
Ultra-Short-Term Load Forecasting for Customer-Level Integrated Energy Systems Based on Composite VTDS Models
Tong Lu, Sizu Hou, Yan Xu
January 5, 2024 (v1)
Keywords: feature selection, integrated energy systems, load forecasting, support vector regression, variational mode decomposition
A method is proposed to address the challenging issue of load prediction in user-level integrated energy systems (IESs) using a composite VTDS model. Firstly, an IES multi-dimensional load time series is decomposed into multiple intrinsic mode functions (IMFs) using variational mode decomposition (VMD). Then, each IMF, along with other influential features, is subjected to data dimensionality reduction and clustering denoising using t-distributed stochastic neighbor embedding (t-SNE) and fast density-based spatial clustering of applications with noise (FDBSCAN) to perform major feature selection. Subsequently, the reduced and denoised data are reconstructed, and a time-aware long short-term memory (T-LSTM) artificial neural network is employed to fill in missing data by incorporating time interval information. Finally, the selected multi-factor load time series is used as input into a support vector regression (SVR) model optimized using the quantum particle swarm optimization (QPSO) a... [more]
Development of Ultrasound Piezoelectric Transducer-Based Measurement of the Piezoelectric Coefficient and Comparison with Existing Methods
Chandana Ravikumar, Vytautas Markevicius
September 21, 2023 (v1)
Keywords: acoustic method, dynamic, energy harvesting, interferometric, piezoelectric coefficient, quasi-static, ultrasound transducer
Energy harvesting using the piezoelectric material in the development of compact vibration energy harvesters can be used as a backup power source for wireless sensors or to fully replace the use of fossil-resource-wasting batteries and accumulators to power a device or sensor. Generally, the coefficient is used as the metric for evaluating the property in materials. Recent research reports that accurate measurement and calculation of the coefficient in materials, especially in polymers, can be challenging for various reasons. From the reviewed references, different methods, including the quasi-static, dynamic, interferometric, and acoustic methods, are discussed and compared based on the direct and indirect effect, accuracy, repeatability, frequency range, and so on. A development of an ultrasound piezoelectric transducer is conducted to estimate d33 coefficient with a reference value. The purpose of the method was mainly to measure the values of piezoelectric material in order to meas... [more]
A Novel Power Quality Comprehensive Estimation Model Based on Multi-Factor Variance Analysis for Distribution Network with DG
Haili Ding, Pengyuan Liu, Xingzhi Chang, Bai Zhang
September 21, 2023 (v1)
Keywords: DG, multi-factor analysis of variance, power quality evaluation, significance testing
The power quality estimation for distribution network connected DG (distributed generation) is important in the power system. The significance testing for power quality indicator is less used in traditional power quality evaluation. However, the power quality indicator is affected by various factors of the power system, which seriously impact the power quality evaluation result. To solve this problem, A novel power quality comprehensive estimation model based on multi-factor variance analysis for distribution network with DG is proposed in this paper, in which the significance testing is carried out for power quality indicator with the various system factors, and then to generate the evaluation weights in different levels, further to obtain the power quality assessment results for single node. And then, the dual-significance tests are carried out to generate the weight of node and to obtain the comprehensive estimation result of whole system. At last, an example is developed to validat... [more]
Electric Vehicle Charging Load Prediction Model Considering Traffic Conditions and Temperature
Jiangpeng Feng, Xiqiang Chang, Yanfang Fan, Weixiang Luo
September 20, 2023 (v1)
Keywords: electric vehicles, load forecasting, Monte Carlo method, spatio-temporal distribution, traffic conditions
The paper presents a novel charging load prediction model for electric vehicles that takes into account traffic conditions and ambient temperature, which are often overlooked in conventional EV load prediction models. Additionally, the paper investigates the impact of disordered charging on distribution networks. Firstly, the paper creates a traffic road network topology and speed-flow model to accurately simulate the driving status of EVs on real road networks. Next, we calculate the electric vehicle power consumption per unit kilometer by considering the effects of temperature and vehicle speed on electricity consumption. Then, we combine the vehicle’s main parameters to create a single electric vehicle charging model, use the Monte Carlo method to simulate electric vehicle travel behavior and charging, and obtain the spatial and temporal distribution of total charging load. Finally, the actual traffic road network and typical distribution network in northern China are used to analyz... [more]
Optimal Allocation Method of Circuit Breakers and Switches in Distribution Networks Considering Load Level Variation
Guodong Huang, Yi Zhou, Chen Yang, Qiong Zhu, Li Zhou, Xiaofeng Dong, Junting Li, Junpeng Zhu
September 20, 2023 (v1)
Keywords: allocation, circuit breakers, distribution network, load level variation, reliability enhancement, switches
Reliability is a fundamental concept for power systems, and the optimal placement of switchable devices is a valuable tool for improvements in this area. The goal of this paper is to propose an optimal allocation method for circuit breakers and switches that can break the cost−reliability dilemma and simultaneously achieve reliability and economic improvement in terms of the distribution network. Moreover, in view of the fact that variations in the load level can affect the reliability of the distribution network, the variations of different load level scenarios are considered in this paper, where a mixed integer linear programming (MILP) model based on fictitious fault flows is established to derive the optimal allocation scheme that can adapt to the changes of multiple scenarios regarding the load. Meanwhile, due to the constraints of reliability indices, the post-fault reconfiguration scheme of a distribution network under different load level scenarios can also be obtained to enhan... [more]
IMODBO for Optimal Dynamic Reconfiguration in Active Distribution Networks
Naiwei Tu, Zuhao Fan
July 13, 2023 (v1)
Keywords: IMODBO, K-means++, network reconfiguration, renewable energy sources, voltage fluctuations
A dynamic reconfiguration method based on the improved multi-objective dung beetle optimizer (IMODBO) is proposed to reduce the operating cost of the distribution network with distributed generation (DG) and ensure the quality of the power supply, while also minimizing the number of switch operations during dynamic reconfiguration. First, a multi-objective model of distribution network dynamic reconfiguration with the optimization goal of minimizing active power loss and voltage deviation is established. Secondly, the K-means++ clustering algorithm is used to divide the daily load of the distribution network into periods. Finally, using the IMODBO algorithm, the distribution network is reconstructed into a single period. The IMODBO algorithm uses the chaotic tent map to initialize the population, which increases the ergodicity of the initial population and solves the problem of insufficient search space. The algorithm introduces an adaptive weight factor to solve the problem of the alg... [more]
Blank Strip Filling for Logging Electrical Imaging Based on Multiscale Generative Adversarial Network
Qifeng Sun, Naiyuan Su, Faming Gong, Qizhen Du
July 7, 2023 (v1)
Keywords: blank strip filling, electrical imaging logging, GAN, U-Net
The Fullbore Formation Micro Imager (FMI) represents a proficient method for examining subterranean oil and gas deposits. Despite its effectiveness, due to the inherent configuration of the borehole and the logging apparatus, the micro-resistivity imaging tool cannot achieve complete coverage. This limitation manifests as blank regions on the resulting micro-resistivity logging images, thus posing a challenge to obtaining a comprehensive analysis. In order to ensure the accuracy of subsequent interpretation, it is necessary to fill these blank strips. Traditional inpainting methods can only capture surface features of an image, and can only repair simple structures effectively. However, they often fail to produce satisfactory results when it comes to filling in complex images, such as carbonate formations. In order to address the aforementioned issues, we propose a multiscale generative adversarial network-based image inpainting method using U-Net. Firstly, in order to better fill the... [more]
Data-Driven Operation of Flexible Distribution Networks with Charging Loads
Guorui Wang, Zhenghao Qian, Xinyao Feng, Haowen Ren, Wang Zhou, Jinhe Wang, Haoran Ji, Peng Li
July 4, 2023 (v1)
Keywords: charging loads, data-driven operation, flexible distribution networks (FDNs), multi-timescale coordination, soft open point (SOP)
The high penetration of distributed generators (DGs) and the large-scale charging loads deteriorate the operational status of flexible distribution networks (FDNs). A soft open point (SOP) can deal with operational issues, such as voltage violations and the high electricity purchasing cost of charging stations. However, the absence of accurate parameters poses challenges to model-based methods. This paper proposes a data-driven operation method of FDNs with charging loads. First, a data-driven model-free adaptive predictive control (MFAPC) approach is proposed to fully involve charging loads in the control of FDN without accurate network parameters. Then, a multi-timescale coordination control model of an SOP with charging loads is established to satisfy the demand of charging loads and improve the control performance. The effectiveness of the proposed method is numerically demonstrated on the modified IEEE 33-node distribution network. The results indicate that the proposed method can... [more]
Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems
Dallatu Abbas Umar, Gamal Alkawsi, Nur Liyana Mohd Jailani, Mohammad Ahmed Alomari, Yahia Baashar, Ammar Ahmed Alkahtani, Luiz Fernando Capretz, Sieh Kiong Tiong
June 13, 2023 (v1)
Keywords: Artificial Intelligence, MPPT, wind energy harvesting system
As wind energy is widely available, an increasing number of individuals, especially in off-grid rural areas, are adopting it as a dependable and sustainable energy source. The energy of the wind is harvested through a device known as a wind energy harvesting system (WEHS). These systems convert the kinetic energy of wind into electrical energy using wind turbines (WT) and electrical generators. However, the output power of a wind turbine is affected by various factors, such as wind speed, wind direction, and generator design. In order to optimize the performance of a WEHS, it is important to track the maximum power point (MPP) of the system. Various methods of tracking the MPP of the WEHS have been proposed by several research articles, which include traditional techniques such as direct power control (DPC) and indirect power control (IPC). These traditional methods in the standalone form are characterized by some drawbacks which render the method ineffective. The hybrid techniques com... [more]
Optimization Strategy of the Electric Vehicle Power Battery Based on the Convex Optimization Algorithm
Xuanxuan Wang, Wujun Ji, Yun Gao
June 7, 2023 (v1)
Keywords: convex optimization algorithm, electric vehicle, energy management strategy, motor model, power battery
With the development of the electric vehicle industry, electric vehicles have provided more choices for people. However, the performance of electric vehicles needs improvement, which makes most consumers take a wait-and-see attitude. Therefore, finding a method that can effectively improve the performance of electric vehicles is of great significance. To improve the current performance of electric vehicles, a convex optimization algorithm is proposed to optimize the motor model and power battery parameters of electric vehicles, improving the overall performance of electric vehicles. The performance of the proposed convex optimization algorithm, dual loop DP optimization algorithm, and nonlinear optimization algorithm is compared. The results show that the hydrogen consumption of electric vehicles optimized by the convex optimization algorithm is 95.364 g. This consumption is lower than 98.165 g of the DCDP optimization algorithm and 105.236 g of the nonlinear optimization algorithm bef... [more]
Investigating the Power of LSTM-Based Models in Solar Energy Forecasting
Nur Liyana Mohd Jailani, Jeeva Kumaran Dhanasegaran, Gamal Alkawsi, Ammar Ahmed Alkahtani, Chen Chai Phing, Yahia Baashar, Luiz Fernando Capretz, Ali Q. Al-Shetwi, Sieh Kiong Tiong
June 7, 2023 (v1)
Keywords: deep learning, hybrid model, long short-term memory, photovoltaic power forecasting, Renewable and Sustainable Energy, solar irradiance forecasting
Solar is a significant renewable energy source. Solar energy can provide for the world’s energy needs while minimizing global warming from traditional sources. Forecasting the output of renewable energy has a considerable impact on decisions about the operation and management of power systems. It is crucial to accurately forecast the output of renewable energy sources in order to assure grid dependability and sustainability and to reduce the risk and expense of energy markets and systems. Recent advancements in long short-term memory (LSTM) have attracted researchers to the model, and its promising potential is reflected in the method’s richness and the growing number of papers about it. To facilitate further research and development in this area, this paper investigates LSTM models for forecasting solar energy by using time-series data. The paper is divided into two parts: (1) independent LSTM models and (2) hybrid models that incorporate LSTM as another type of technique. The Root me... [more]
Computational Study of Security Risk Evaluation in Energy Management and Control Systems Based on a Fuzzy MCDM Method
Wajdi Alhakami
June 7, 2023 (v1)
Keywords: communication network, multiple criteria decision-making, power control system, security evaluation, security risk
Numerous cyberattacks on connected control systems are being reported every day. Such control systems are subject to hostile external attacks due to their communication system. Network security is vital because it protects sensitive information from cyber threats and preserves network operations and trustworthiness. Multiple safety solutions are implemented in strong and reliable network security plans to safeguard users and companies from spyware and cyber attacks, such as distributed denial of service attacks. A crucial component that must be conducted prior to any security implementation is a security analysis. Because cyberattack encounters in power control networks are currently limited, a comprehensive security evaluation approach for power control technology in communication networks is required. According to previous studies, the challenges of security evaluation include a power control process security assessment as well as the security level of every control phase. To address... [more]
Adaptive Control Strategy for Stationary Electric Battery Storage Systems with Reliable Peak Load Limitation at Maximum Self-Consumption of Locally Generated Energy
Florian Klausmann, Anna-Lena Klingler
May 26, 2023 (v1)
Keywords: BESS, charge management, control strategy, economic optimization, energy management, peak load limitation, peak-shaving, self-consumption, stationary battery
Nowadays, stationary battery storage systems are generally used to optimize the self-consumption of electricity generated locally or to limit the peak load of the local grid connection. Self-consumption optimization aims to achieve economic benefits by using more of the self-generated electricity within the local grid. Batteries used for the optimization of self-consumption tend to present low states of charge and, therefore, normally do not contribute to peak load limitation. Peak load limitation is used to minimize the grid connection power to enable more cost-efficient grid connections. However, this function can only be achieved year-round if there is sufficient surplus electricity production or if the battery can be charged from the grid. In the latter case, the batteries are often fully charged and do not significantly optimize the self-consumption. This study presents a new operating strategy that combines all the advantages of the previous operating modes with none of the disad... [more]
Consumer Preferences for Smart Energy Services Based on AMI Data in the Power Sector
Hye-Jeong Lee, Beom Jin Chung, Sung-Yoon Huh
May 26, 2023 (v1)
Keywords: choice experiment, smart energy service, stated preference techniques, willingness to pay
Advanced metering infrastructure (AMI) is becoming increasingly popular as an efficient means of energy demand management. By collecting energy data through AMI, it is possible to provide users with information that can induce them to change their behavior. To ensure that AMI continues to expand and to encourage the use of energy data, it is important to increase consumer participation and analyze their preferred service attributes. This study utilized a choice experiment to analyze consumer preferences for and acceptance of smart energy services based on AMI data. The results of a mixed logit model estimation show that consumers prefer the electricity information service for individual households and the social safety-net service among convergence services. A scenario analysis confirms that monetary compensation to offset any additional charges is important to maintain the level of consumer acceptance. These empirical findings offer insights for policymakers and companies seeking to d... [more]
Power Distribution System Outage Management Using Improved Resilience Metrics for Smart Grid Applications
Arif Fikri Malek, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Jasrul Jamani Jamian, Li Wang, Munir Azam Muhammad
May 24, 2023 (v1)
Keywords: distribution systems, mobile emergency generators, network reconfiguration, resilience metrics, smart grid
Smart grid systems play a significant role in improving the resilience of distribution systems (DSs). In this paper, two strategies are proposed for implementation of a smart grid application: (a) a network reconfiguration and (b) a network reconfiguration with mobile emergency generator (MEGs) deployment. An improved set of resilience metrics to quantify and enhance the resiliency of distribution systems (DSs) is developed for the proposed optimization. The metrics aim to determine a suitable strategy and the optimal number and capacity of MEGs to restore the disconnected loads through the development of several microgrids. These metrics are then aggregated with the proposed strategy to develop an automated solution provider. The objective is to maximize system resilience considering the priority loads. The proposed resilience metrics are tested on the IEEE 33-Bus radial DSs. The case studies conducted proved the performance of the proposed power outage management strategy and resilie... [more]
Energy Management Strategies of Grid-Connected Microgrids under Different Reliability Conditions
Mohammed Abdullah H. Alshehri, Youguang Guo, Gang Lei
May 24, 2023 (v1)
Keywords: Algorithms, battery storage, energy management, microgrid, reliability, solar
The demand for a reliable, cheap and environmentally friendly source of energy makes the integration of renewable energy into power networks a global challenge. Furthermore, reliability, as one of the core elements of efficient and cost-effective energy management options, is still among the dominant factors/techniques that receive more attention for realistic penetrations of renewable energy into the electricity grid. This paper proposes an efficient way of energy management for a grid-connected microgrid. The grid-connected microgrid used in the analysis consists of solar photovoltaic (P.V.) and battery. In this microgrid configuration, oftentimes, the output power might not be equal to the system demand; in this regard, it is expected that the mismatch between these output powers is not zero. However, to reduce the mismatch between demand and supply to be close to zero, this paper proposes strategies of increasing the rated power of solar, battery and grid separately and combining t... [more]
The Role of Mild Alkaline Pretreatment in the Biorefinery Upgrade of Spent Coffee Grounds
Gabriel Mota Ribeiro, Pedro L. Martins, Ana Cristina Oliveira, Florbela Carvalheiro, Rita Fragoso, Luís C. Duarte
May 24, 2023 (v1)
Keywords: biogas, biomass pretreatment, circular bioeconomy, lignin-derived products, oligosaccharides
This work proposes a valorization route for spent coffee grounds (SCG), a widespread lignocellulosic residue, encompassing the production of: biomethane, lignin, and oligosaccharides as value-added products obtained simultaneously during a mild alkaline (NaOH) pretreatment. The studied operational variables were the reaction time (60−240 min), temperature (25−75 °C), and the NaOH concentration (0−2.5 M). The severity factor suitably describes the global process kinetics, with higher severities (log Mo = 5.5) yielding high product yields, 18.02% and 13.25% (on dry SCG basis) for lignin and oligosaccharides (XGMOS), respectively. Solid yield is negatively impacted by all studied variables (at the 95% confidence level). Conversely, XGMOS yield is positively influenced both by time and catalyst concentration, whereas lignin yield is only (positively) influenced by catalyst concentration. Optimal balance between product formation and potential operational costs is putatively achieved when u... [more]
Potentialities and Impacts of Biomass Energy in the Brazilian Northeast Region
Edvaldo Pereira Santos Júnior, Elias Gabriel Magalhães Silva, Maria Helena de Sousa, Emmanuel Damilano Dutra, Antonio Samuel Alves da Silva, Aldo Torres Sales, Everardo Valadares de Sa Barretto Sampaio, Luiz Moreira Coelho Junior, Rômulo Simões Cezar Menezes
May 24, 2023 (v1)
Keywords: bioeconomy, bioenergy, biomass emissions, biomass resources, regional economy
In Northeast Brazil, the use of biomass for energy generation is settled on traditional productive arrangements, such as a sugarcane production system in the humid Atlantic coastal area and firewood extraction from native tropical dry forests in the west. In parallel, substantial amounts of other biomass sources, such as residues from agricultural or urban processes, are still little used or wholly wasted, fudging the opportunity to generate new value chains based on these biomass sources. We hypothesize that using these non-traditional biomass sources to produce biofuels would significantly increase the regional bioenergy supply. In this context, this article discusses the potential for the production and use of biofuels and bioenergy in Northeast Brazil and its effects on regional development, which may be useful for both private actors and policymakers in the energy sector. The use of biomass sources for energy in the region is significant, reaching approximately 8.8 million tons of... [more]
Optimal Sizing of Battery and Super-Capacitor Based on the MOPSO Technique via a New FC-HEV Application
Abdeldjalil Djouahi, Belkhir Negrou, Boubakeur Rouabah, Abdelbasset Mahboub, Mohamed Mahmoud Samy
May 24, 2023 (v1)
Keywords: energy management strategy, fuel-cell hybrid electric vehicle, hydrogen consumption, multi-objective function problem, particle swarm optimization algorithm
In light of the energy and environment issues, fuel cell vehicles have many advantages, including high efficiency, low-temperature operation, and zero greenhouse gas emissions, making them an excellent choice for urban environments where air pollution is a significant problem. The dynamics of fuel cells, on the other hand, are relatively slow, owing principally to the dynamics of the air compressor and the dynamics of manifold filling. Because these dynamics can limit the overall performance of fuel cell vehicles, two key technologies that have emerged as critical components of electric vehicle powertrains are batteries and supercapacitors. However, choosing the best hybrid energy storage system that combines a battery and a supercapacitor is a critical task nowadays. An electric vehicle simulated application by MATLAB Code is modeled in this article using the multi-objective particle swarm optimization technique (MOPSO) to determine the appropriate type of batteries and supercapacitor... [more]
Method of Site Selection and Capacity Setting for Battery Energy Storage System in Distribution Networks with Renewable Energy Sources
Simin Peng, Liyang Zhu, Zhenlan Dou, Dandan Liu, Ruixin Yang, Michael Pecht
May 24, 2023 (v1)
Keywords: battery energy storage system, Genetic Algorithm, simulated annealing algorithm, site selection and capacity setting
The reasonable allocation of the battery energy storage system (BESS) in the distribution networks is an effective method that contributes to the renewable energy sources (RESs) connected to the power grid. However, the site and capacity of BESS optimized by the traditional genetic algorithm is usually inaccurate. In this paper, a power grid node load, which includes the daily load of wind power and solar energy, was studied. Aiming to minimize the average daily distribution networks loss with the power grid node load connected with RESs, a site selection and capacity setting model of BESS was built. To solve this model, a modified simulated annealing genetic algorithm was developed. In the developed method, the crossover probability and the mutation probability were modified by a double-threshold mutation probability control, which helped this genetic method to avoid trapping in local optima. Moreover, the cooling mechanism of simulated annealing method was presented to accelerate the... [more]
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