Hasil untuk "Renewable energy sources"

LI Zhenxing, YANG Zikang, YANG Guang et al.

This paper examines the declining adaptability of conventional relay protection systems caused by large-scale renewable energy integration. A systematic review is conducted on fault characteristics of different renewable energy sources and corresponding protection improvement strategies. Through comparative analysis of dynamic characteristics between renewable energy systems （wind/photovoltaic） and conventional synchronous generators， the study identifies key challenges introduced by power electronic devices： limited fault current amplitude， controlled phase response， and increased harmonic complexity. Building upon existing research achievements， this paper conducts an in-depth exploration of renewable energy equivalent modeling and its application value in fault characteristic research， while systematically analyzing the causes behind the degraded adaptability of conventional protection schemes such as pilot differential protection and distance protection in renewable energy scenarios. The analysis reveals that although existing improved solutions have enhanced protection performance through innovative principles including transient voltage-based phase selection， bilateral fault information similarity， and transient energy differential， they remain fundamentally constrained by technical limitations： the strong coupling with control strategies， complexity operating conditions， and difficulties in reclosing coordination. Future reasearch needs to further explore： 1） The intrinsic relationship between renewable energy control strategies and transient fault characteristics； 2） The establishment of a multi-dimensional fault feature extraction system； 3） Theoretical breakthroughs through integration of control links with conventional protection. The paper concludes with technical prospects for protection technology development， providing references for secure opeation of modern power systems.

Su-Seong Park, Rae-Young Kim, Dong-Geun Lee

In this paper, a droop-based distributed control method is proposed to enhance the penetration rate of renewable energy sources and minimize low-voltage fluctuations within the DC local grid. The proposed method designs droop gains for state of charge (SoC)-based droop control considering line impedance and other parameters in the DC local grid, thereby facilitating precise SoC equalization among different energy storage systems (ESS) considering the dc bus voltage fluctuation and power sharing of each component. Further, the proposed technique applies droop control to the grid-connected converter considering the SoC of ESS, enabling effective power distribution between the AC grid and ESS based on the magnitude of SoC. Secondary voltage compensation control is performed by integrating the structure of ramp rate control into this control method for DC bus voltage control, which helps alleviate excessive output fluctuations of renewable energy sources. The proposed method can be applied based on the SoC of ESS, thereby achieving a 56.56% improvement in the penetration rate of renewable energy. In addition, the DC bus voltage fluctuation is controlled within 1%, and SoC equalization is achieved when operating more than two ESS units in DC local grid system. The validity of the proposed technique is verified using PSCAD/EMTDC simulations and shows improvement on both renewable energy penetration rate and voltage fluctuation.

Branislav Šarkan, Jacek Caban, Arkadiusz Małek et al.

The article contains an analysis of power generation by a photovoltaic system with a peak power of 3 MWp and a wind turbine with a power of 3.45 MW. The acquired time series of generated power was analyzed using traditional and modern analytical methods. The power generated by these two Renewable Energy Sources was characterized separately and then by their mix. In this article, the power signature was defined as the power generated by the photovoltaic system and the wind turbine in the state space over a period of one month. The state space was extracted from the results of cluster analysis. The experiment with clustering was carried out into 10 classes. The K-Means clustering algorithm was used to determine the clusters in a variant without prior labeling of classes with the method of learning without the participation of the teacher. In this way, the trajectories of the power generation process from two Renewable Energy Sources were determined in the 10-state space. Knowing which class each data record belongs to, the frequencies of staying in each state were determined. The computational algorithm presented in the article may have great practical application in balancing the power grid powered by energy produced from renewable sources.

Kommoju Naga Durga Veera Sai Eswar, M. Arun Noyal Doss, Mohammad Shorfuzzaman et al.

Microgrid-equipped electric vehicle charging stations offer economical and sustainable power sources. In addition to supporting eco-friendly mobility, the technology lowers grid dependency and improves energy reliability. The manuscript introduces a hybrid technique for efficient electric vehicle (EV) charging integrating the Dollmaker Optimization algorithm (DOA) and spatial Bayesian neural network (SBNN). This method optimizes the joint operation of photovoltaic (PV), wind turbines (WTs), supercapacitors (SCs), and battery energy storage systems (BESSs) in microgrids to enhance EV charging station efficiency, reliability, and power quality while reducing grid outages. The SBNN predicts EV load demand for improved efficiency and reliability, while DOA manages microgrid (MG) fluctuations to ensure seamless EV charging. The MG system features a four-phase inductor coupled interleaved boost converter (FP-ICIBC) and a fractional-order proportional-integral-derivative (FOPID) controller for optimal power management. An evaluation in MATLAB compares DOA–SBNN with existing approaches, demonstrating its effectiveness in enhancing EV charging performance. The proposed method outperforms all current techniques, including the Multi swarm Optimization (MSO), the Multi-Objective Gray Wolf Optimizer (MOGWO), and the Modified Multi-objective Salp Swarm Optimization algorithm (MMOSSA). The results show that the energy efficiency of the recommended approach is 19.19%, 26.15%, and 32.57% higher than the three current techniques, respectively, and that of total harmonic distortion (THD) is 19.09%, 25.85%, and 31.17% lower than those three techniques, respectively.

Bistoon Hosseini

This article discusses forecasting the monthly electricity consumption time series of household subscribers using the similar pattern algorithm, which uses each subscriber’s unique consumption pattern. The primary goal of forecasting the monthly consumption of household subscribers is to issue monthly bills and cluster subscribers for consumption management planning. The study’s results demonstrate the efficiency of the proposed algorithm compared to traditional statistics and machine learning methods. Out of the 72,000 predictions made using the proposed algorithm, the mean absolute percentage error is 16.9%. This shows that the algorithm successfully forecasts the monthly consumption of subscribers. The similar pattern algorithm maximizes the use of information in the billing database and takes advantage of expert opinions, which play a crucial role in avoiding unusual forecasts. The household subscribers involved in this study are located in two climatic regions: temperate and tropical. As this study has shown a significant dependency of household electricity consumption on the two major climate types, the obtained results have the potential to be generalized to other climatic regions as well.

Jianjun Zhu, Yongquan Zhou, Yuanfei Wei et al.

For the classical multi-objective optimal power flow (MOOPF) problem, only traditional thermal power generators are used in power systems. However, there is an increasing interest in renewable energy sources and the MOOPF problem using wind and solar energy has been raised to replace part of the thermal generators in the system with wind turbines and solar photovoltaics (PV) generators. The optimization objectives of MOOPF with renewable energy sources vary with the study case. They are mainly a combination of 2–4 objectives from fuel cost, emissions, power loss and voltage deviation (VD). In addition, reasonable prediction of renewable power is a major difficulty due to the discontinuous, disordered and unstable nature of renewable energy. In this paper, the Weibull probability distribution function (PDF) and lognormal PDF are applied to evaluate the available wind and available solar power, respectively. In this paper, an enhanced multi-objective mayfly algorithm (NSMA-SF) based on non-dominated sorting and the superiority of feasible solutions is implemented to tackle the MOOPF problem with wind and solar energy. The algorithm NSMA-SF is applied to the modified IEEE-30 and standard IEEE-57 bus test systems. The simulation results are analyzed and compared with the recently reported MOOPF results.

Haibo Zhang, Houyu Qi, Shuai Wang

A robust distributed state estimation algorithm for AC/DC system with AC tie lines and high voltage direct current (LCC-HVDC) tie lines is proposed. The proposed algorithm consists of robust DC state estimation in the coordinator and robust distributed AC state estimation, and implements sequential solving by exchanging coupling variables of the AC/DC system. For AC state estimation, a distributed state estimation algorithm based on the bilinear algorithm is designed, which can achieve the same accuracy as the centralized algorithm. Robust state estimator based on the exponential absolute value function and exponential square function is suitable for reducing the influence of outliers and can reduce the operation scale by simplifying the nonlinear iterative process in distributed state estimation. Finally, the correctness and effectiveness of the algorithm is verified by simulation of three IEEE 118 bus systems interconnected through AC/DC hybrid tie lines.

Richard Schalinski, Paula Mörstedt, Stefan L. Schweizer et al.

Silicon–air batteries (SABs) are attracting significant attention for their potential as high‐energy‐density electrochemical storage devices. One of the main limitations for the commercial use of alkaline SABs is the high corrosion, which results in a low conversion efficiency. Herein, the aim is to examine the influence of polyethylene glycol (PEG) on the conversion efficiency of SABs, shedding light on key factors affecting their performance. SABs using KOH as electrolyte at two concentrations, 0.5 and 2.0 mol L−1, are investigated. The results show that replacing part of the water in the alkaline electrolyte with PEG changes the etching behavior from anisotropic to polishing and increases the specific energy density by 53% and 123% in 0.5 and 2 mol L−1 KOH electrolytes, respectively.

Yongkang Ding, Xinjiang Chen, Jianxiao Wang

The joint optimization of power systems, mobile energy storage systems (MESSs), and renewable energy involves complex constraints and numerous decision variables, and it is difficult to achieve optimization quickly through the use of commercial solvers, such as Gurobi and Cplex. To address this challenge, we present an effective joint optimization approach for MESSs and power grids that consider various renewable energy sources, including wind power (WP), photovoltaic (PV) power, and hydropower. The integration of MESSs could alleviate congestion, minimize renewable energy waste, fulfill unexpected energy demands, and lower the operational costs for power networks. To model the entire system, a mixed-integer programming (MIP) model was proposed that considered both the MESSs and the power grid, with the goal of minimizing costs. Furthermore, this research proposed a highly efficient deep reinforcement learning (DRL)-based method to optimize route selection and charging/discharging operations. The efficacy of the proposed method was demonstrated through many numerical simulations.

Cheng ZHONG, Di ZHAI, Yang LU et al.

To address the problem of reduced communication quality in narrow underground power pipe gallery, where wireless sensor network coverage is affected by irregular shapes, obstacles, and electromagnetic interference, a power monitoring coverage sensing model is constructed based on the minimum access rate constraint, and an improved gray wolf coverage optimization algorithm is proposed by combining neuron mapping and differential evolution. Firstly, a uniform initial population is generated by neuron chaos mapping. Then, the nonlinear convergence factor is used to balance the global and local search ability. And finally, a differential evolution algorithm is introduced to mutate the gray wolf individuals. A comparative simulation analysis is made of various coverage optimization methods, and the results show that the proposed algorithm has robust search capabilities and it can significantly improve the network coverage performance in the narrow underground power pipe galleries, while effectively satisfying the communication needs of the monitored nodes.

Bilawal Rehman, Chongru Liu, Huan Li et al.

This paper provides a comprehensive analysis of local and concurrent commutation failure (CF) of multi-infeed high-voltage direct current (HVDC) system considering multi-infeed interaction factor (MIIF). The literature indicates that the local CF is not influenced by MIIF, whereas this paper concludes that both the local CF and concurrent CF are influenced by MIIF. The ability of remote converter to work under reduced reactive power enables its feature to support local converter via inter-connection link. The MIIF measures the strength of electrical connectivity between converters. Higher MIIF gives a clearer path to remote converter to support local converter, but at the same time, it provides an easy path to local converter to disturb remote converter under local fault. The presence of nearby converter increases the local commutation failure immunity index (CFII) while reducing concurrent CFII. Higher MIIF causes reactive power support to flow from remote converter to local converter, which reduces the chances of CF. A mathematical approximation to calculate the increase in local CFII for multi-infeed HVDC configurations is also proposed. A power flow approach is used to model the relation between MIIF and reactive power support from remote end. The local and concurrent CFIIs are found to be inverse to each other over MIIF; therefore, it is recommended that there is an optimal value of MIIF for all converters in close electric proximity to maintain CFII at a certain level. The numerical results of established model are compared with PSCAD/EMTDCsimulations. The simulation results show the details of the influence of MIIF on local CF and concurrent CF of multi-infeed HVDC, which validates the analysis presented.

Yeken A. Sanusi

Cities are unique centers of energy demand and greenhouse gas emissions. Although electricity provides multiple functions for urban residents, its supply in Nigerian urban centers is poor, and the attempts to understand this problem have been limited to national level. Therefore, this study aims to explore the dimensions of electricity supply problem; assess adaptations by households to inadequate electricity supply; examine the use of renewable energy-related facilities; and understand the perception of renewables by urban households, with five residential neighborhoods in Minna, the capital of Niger state, were covered. Data were collected using a questionnaire and the Facility Observatory Technique to document daily electricity supply to households. The collected data covered electricity connection, daily supply, adaptations to inadequate public supply, perception of renewable energy and willingness to shift to renewable electricity sources. Results indicate that households in Minna have an average of 5 hours of electricity daily, while only 25% have electricity at night (7.00pm and 10.00pm.). An index derived to demonstrate the nature of electricity supply to households indicates that the city has a darkness index of 0.81, indicating a situation of extreme inadequacy of electricity supply. The index has a 95% correlation with the proportion of households without electricity at night. The study also shows that 72% of the households use fossil fuel-driven plants while 84% are not familiar with the use of renewable resources for generating electricity. The paper holds that the willingness of the public to switch to renewable energy, the incremental nature of urban development, and the high costs incurred by households for non-sustainable alternative sources of electricity provide the foundation for a more concerted effort to develop renewable energy as a means of improving the availability of electricity in Nigerian urban centers.

Tarkhanova Elena, Lyapuntsova Elena, Baburina Natalia et al.

In the recent years, renewable energy is the most actively developing area in the energy industry. The energy decarbonization and the desire to meet the Paris Climate Agreement criteria are the dominant motives of this development. Climate and energy policies, new technologies, changing prices for gas, coal and carbon, the growth of renewable energy sources continue to challenge operators, developers and utility company in energy system. Our article is devoted to these problematic issues. They are related to the renewable energy development. It is a promising direction of “green” growth around the world, including Russia. We discuss the latest trends and developments in the field of renewable energy in Russia in the conditions of global challenges. In addition, we extrapolate possible directions for the renewable energy growth in the future. Our results can be interesting and useful for researchers and experts in the strategic management field, spatial development, innovation economy and some stakeholders involved in the environment and energy system.

Richard C. Lupton, Robin S. Langley

Abstract While detailed aero‐servo‐hydro‐elastic simulation codes for modelling floating wind turbines (FWTs) are available, they achieve high accuracy at the expense of calculation speed. For conceptual design and optimisation, fast solutions are needed, and equivalent linearisation techniques combined with frequency‐domain analysis offers to capture the complex behaviour of FWTs in fast, approximate models. The main aim of this paper is to apply a harmonic linearisation approach to model the aerodynamic loading within a complete coupled model of a FWT, quantifying its performance, and where accuracy is unsatisfactory, to give insight into the causes. Two linearised models are derived from a coupled nonlinear aero‐hydro‐servo‐elastic model, using the OC3‐Hywind FWT as a test case: the typical tangent linearisation derived by numerical perturbation of the nonlinear model and the harmonic linearisation yielding improved representation of the aerodynamic loads. Comparisons against nonlinear time‐domain simulations from Bladed show that it is possible to create a frequency‐domain model of a FWT, including a flexible structure, aeroelastic rotor loads and the effect of the control system, with reasonable accuracy. The biggest source of errors is the presence of additional harmonics caused by nonlinear interactions between loads at different frequencies, rather than inaccurate linearisation of the magnitudes of forces. The computational cost of the harmonic linearisation implemented varies, but in most cases is ∼10× slower than the tangent linearisation and ∼100× faster than the time domain solution.

A. Abid, A. Zouhri, M. Sennoune

L’industrie de textile au Maroc est une industrie qui engendre des déchets liquides et solides polluants, et qui coûte chère non seulement à l’industriel, mais aussi à la collectivité nationale. Donc au contribuable: une augmentation des coûts de production d’eau potable; un épuisement de certaines réserves naturelles et une dégradation d’un capital environnemental. Ces polluants doivent être traités à la source à l’aide des stations de pré traitement avant leur évacuation dans le milieu récepteur. Dans cette étude, nous nous intéressons d’une part, à la mise en application de jus cactus (Opuntia ficus indica) en tant que bio floculant utilisée dans le traitement par procédé coagulation-floculation [1-4] et d’autre part à l’évaluation de traitement par des coagulants et floculants industriels au niveau d’une station de traitement d’une unité de textile. Le traitement par le cactus est simple; il est réalisé en deux étapes principales. L’ajustement de pH avec la chaux et/ou l’acide sulfurique, puis la floculation avec le jus de cactus. Les paramètres qui ont été étudiés au cours de ce travail sont le pH, la MES, la DCO et l’absorbance des colorants de rejets textiles. Les résultats de l’étude comparative entre les deux traitements montrent une efficacité remarquable de traitement par le cactus par apport les produits utilisées dans la station. En effet, le taux d’élimination des colorants passe de 94 % à 97 %, le pourcentage d’abattement de la matière en suspension MES passe de 73 % à 83 % et l’élimination de la DCO de 48 % à 62 %.

Héctor Miguel Aviña Jiménez, Gabriel León de los Santos, Miguel Ángel Benítez Torreblanca

In this article, the comparison of the energetic performance of a binary cycle and a modified binary cycle with flash evaporation is presented, both using a low-enthalpy geothermal resource. The comparative analysis is based on two main discourses: the first one evaluates a conventional binary cycle (CBC) with isopentane as working fluid in order to validate and compare the generated data with those reported in similar studies; the second one uses the same input parameters for both cycles, obtaining the cases in which the modified binary cycle is the most viable choice to use. In addition to the above, several aspects are considered when selecting the most suitable working fluid, and the use of water as working fluid is introduced. When the temperature of the geothermal resource is below 140 °C, and the ambient temperature is 25 °C, the flash evaporation binary cycle, using water as working fluid, shows an improved performance compared to a CBC, with a theoretical output over 1000 kWe. This may encourage new areas of opportunity for power generation, not only with low- and medium-enthalpy geothermal energy, but also with other renewable energy sources such as solar.

Adam Fenech

<p>The leading authority on climate change, the Intergovernmental Panel on Climate Change (IPCC) has<br />concluded that warming of the climate system is unequivocal, and will continue for centuries. The regions<br />in the Middle East and Northern Africa (MENA) have experienced numerous extreme climate events over<br />the past few years including the 2009 flooding in Jeddah, Kingdom of Saudi Arabia; the 2005 dust storm<br />in Al Asad, Iraq; water scarcity throughout the Arab MENA; and the rising sea levels on the Nile Delta<br />coast, Egypt. A climate baseline can be developed for regions in the MENA by locating climate stations in<br />the study area using observations made in the Global Climate Observing System (GCOS). For projections<br />of future climate, global climate models (GCMs), mathematical equations that describe the physics, fluid<br />motion and chemistry of the atmosphere, are the most advanced science available. The Climate Research<br />Lab at the University of Prince Edward Island has a dataset available to researchers, called the Climate,<br />Ocean and Atmosphere Data Exchange (COADE), that provides easy access to the output from forty<br />global climate models used in the deliberations of the Intergovernmental Panel on Climate Change’s<br />(IPCC) Fifth Assessment Report (AR5) including monthly global climate model projections of future climate<br />change for a number of climate parameters including temperature and precipitation. Over the past 50<br />years, climate changes in the MENA Region have led to increases in annual mean temperatures and<br />decreases in annual total precipitation. Applying all four greenhouse gas emission futures on a base<br />climate normal of 1981-2010 to an ensemble of forty global climate models used in the Fifth Assessment<br />Report of the Intergovernmental Panel on Climate Change (IPCC AR5) results in future temperature<br />increases for the MENA Region ranging from 1.6 to 2.3 degrees Celsius, and in a range of future<br />precipitation changes from reductions of 11 percent to increases of 36 percent by the 2050s (2041-2070).<br />These preliminary results should assist the MENA Region in planning its energy needs and its needs for<br />renewable energy through increasing the understanding of how climate has impacted the region in the<br />past, and how climate will impact in the future.</p><p> </p>

L. Merabti, M. Merzouk, N. Kasbadji et al.

Le développement des systèmes de climatisation a un impact environnemental de plus en plus important de par leurs consommations énergétiques. Le ‘dessiccant cooling’ représente une technologie innovante permettant de rafraîchir une ambiance par les changements d’état de l’eau et l’exploitation de l’énergie solaire. Notre travail consiste en l’étude d’un système de rafraîchissement évaporatif par dessiccation couplé à une installation solaire, permettant ainsi de réduire la consommation électrique et utilisant une énergie propre et gratuite. Les résultats trouvés montrent que le système permet de contrôler l’humidité et fournit donc des conditions de confort acceptables, ce qui confirme qu’il est bien adapté pour des zones humides, telles que les villes côtières de notre pays.

Tianxin Wei, Theodoros Dimopoulos

Maria ANDRONIE, Mihai ANDRONIE

One of the fields whose importance has been surging lately is the durable development, which is impossible to achieve unless humankind gives up gradually to the fossil energy sources and switches to the exploitation of the renewable energy sources.  This shift is mainly due to the fact that the traditional energy sources are limited, pricier and pricier and have a negative and irreversible effect upon the environment. In the durable development area, particularly the renewable energies, there are informatics systems used in a wide range of activities, from investments management and energy sources to the operation itself of their exploitation systems.  Such informatics systems may be integrated at a higher level, as the national weather forecast system or other specific systems.