Innovative association network of new energy vehicle charging stations in China: Structural evolution and policy implications

Heliyon, Год журнала: 2024, Номер 10(2), С. e24764 - e24764

Опубликована: Янв. 1, 2024

New energy vehicles (NEVs) can effectively reduce emissions and alleviate global climate problems, are crucial to sustainable development. China is the world's largest seller of NEVs, but charging stations have always been a major constraint development NEVs. To clearly characterize structural characteristics an innovation association network NEV stations, this study analyzes China's with patent data since 2007 in Incopat Global Patent Database from three perspectives province, city applicant using method social analysis (SNA). The findings show following: (1) has expanded constantly, strength evidently increasing. (2) exhibits typical core-periphery structure, quantity nodes high varying little, low- medium-association strengths exhibiting evident increasing trend. (3) effect regional central cities enhanced, group structure. There no information barrier caused by excessive small formation province network, whereas there trends cooperation networks. In addition, policy recommendations for further expanding technological promote industry discussed based on results.

Язык: Английский

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Optimizing dynamic economic dispatch through an enhanced Cheetah-inspired algorithm for integrated renewable energy and demand-side management

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Фев. 7, 2024

Abstract This study presents the Enhanced Cheetah Optimizer Algorithm (ECOA) designed to tackle intricate real-world challenges of dynamic economic dispatch (DED). These complexities encompass demand-side management (DSM), integration non-conventional energy sources, and utilization pumped-storage hydroelectric units. Acknowledging variability solar wind sources existence a system, this integrates solar-wind-thermal system. The DSM program not only enhances power grid security but also lowers operational costs. research addresses DED problem with without implementation analyze its impact. Demonstrating effectiveness on two test systems, suggested method's efficacy is showcased. recommended simulation results have been compared those obtained using (COA) Grey Wolf Optimizer. optimization indicate that, for both 10-unit 20-unit proposed ECOA algorithm achieves savings 0.24% 0.43%, respectively, in operation costs when Dynamic Economic Dispatch conducted Demand-Side Management (DSM). underscores advantageous capability minimizing enhancing efficiency systems. Our has greater adaptability reliability, making it promising solution addressing multi-objective difficulties within microgrids, particularly demand response mechanisms are incorporated. Furthermore, ability elucidate optimal flow IEEE standard electric vehicles renewable integrated.

Язык: Английский

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A multilayer perceptron neural network approach for optimizing solar irradiance forecasting in Central Africa with meteorological insights

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Фев. 12, 2024

Abstract Promoting renewable energy sources, particularly in the solar industry, has potential to address shortfall Central Africa. Nevertheless, a difficulty occurs due erratic characteristics of irradiance data, which is influenced by climatic fluctuations and challenging regulate. The current investigation focuses on predicting an inclined surface, taking into consideration impact variables such as temperature, wind speed, humidity, air pressure. used methodology for this objective Artificial Neural Network (ANN), inquiry carried out metropolitan region Douala. data collection device research meteorological station located at IUT This was built component Douala sustainable city effort, partnership with CUD IRD. Data collected 30-min intervals duration around 2 years, namely from January 17, 2019, October 30, 2020. aforementioned been saved database that underwent pre-processing Excel later employed MATLAB creation artificial neural network model. 80% available utilized training network, 15% allotted validation, remaining 5% testing. Different combinations input were evaluated ascertain their individual degrees accuracy. logistic Sigmoid function, 50 hidden layer neurons, yielded correlation coefficient 98.883% between observed estimated sun irradiation. function suggested evaluating intensities radiation place being researched other sites have similar conditions.

Язык: Английский

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A new intelligently optimized model reference adaptive controller using GA and WOA-based MPPT techniques for photovoltaic systems

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Март 21, 2024

Recently, the integration of renewable energy sources, specifically photovoltaic (PV) systems, into power networks has grown in significance for sustainable generation. Researchers have investigated different control algorithms maximum point tracking (MPPT) to enhance efficiency PV systems. This article presents an innovative method address problem systems amidst swiftly changing weather conditions. MPPT techniques supply load during irradiance fluctuations and ambient temperatures. A novel optimal model reference adaptive controller is developed designed based on MIT rule seek global without ripples rapidly. The suggested also optimized through two popular meta-heuristic algorithms: genetic algorithm (GA) whale optimization (WOA). These approaches been exploited overcome difficulty selecting adaptation gain MRAC controller. voltage generated study neuro-fuzzy inference system. controller's performance tested via MATLAB/Simulink software under varying temperature radiation circumstances. Simulation carried out using a Soltech 1sth-215-p module coupled boost converter, which powers resistive load. Furthermore, emphasize recommended algorithm's performance, comparative was done between GA WOA conventional incremental conductance (INC) method.

Язык: Английский

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Enhancing grid-connected photovoltaic system performance with novel hybrid MPPT technique in variable atmospheric conditions

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Апрель 8, 2024

Abstract This paper proposes an innovative approach to improve the performance of grid-connected photovoltaic (PV) systems operating in environments with variable atmospheric conditions. The dynamic nature parameters poses challenges for traditional control methods, leading reduced PV system efficiency and reliability. To address this issue, we introduce a novel integration fuzzy logic sliding mode methodologies. Fuzzy enables effectively handle imprecise uncertain data, allowing decision-making based on qualitative inputs expert knowledge. Sliding control, known its robustness against disturbances uncertainties, ensures stability responsiveness under varying Through these methodologies, our proposed offers comprehensive solution complexities posed by real-world dynamics. We anticipate applications across various geographical locations climates. By harnessing synergistic benefits promises significantly enhance reliability presence On grid side, both PSO (Particle Swarm Optimization) GA (Genetic Algorithm) algorithms were employed tune current controller PI (Proportional-Integral) (inverter control). Simulation results, conducted using MATLAB Simulink, demonstrate effectiveness hybrid MPPT technique optimizing system. exhibits superior tracking efficiency, achieving convergence time 0.06 s 99.86%, less oscillation than classical methods. comparison other techniques highlights advantages approach, including higher faster response times. simulation outcomes are analyzed strategies sides (the array side). Both offer effective methods tuning controller. According considered IEEE standards low-voltage networks, total harmonic distortion values (THD) obtained considerably high (8.33% 10.63%, algorithms, respectively). Comparative analyses terms stability, rapid changes.

Язык: Английский

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Collaborative management of environmental pollution and carbon emissions drives local green growth: An analysis based on spatial effects

Environmental Research, Год журнала: 2024, Номер 259, С. 119546 - 119546

Опубликована: Июль 2, 2024

Язык: Английский

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Enhancing MPPT performance for partially shaded photovoltaic arrays through backstepping control with Genetic Algorithm-optimized gains

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Фев. 9, 2024

As the significance and complexity of solar panel performance, particularly at their maximum power point (MPP), continue to grow, there is a demand for improved monitoring systems. The presence variable weather conditions in Maroua, including potential partial shadowing caused by cloud cover or urban buildings, poses challenges efficiency This study introduces new approach tracking Global Maximum Power Point (GMPP) photovoltaic systems within context research conducted Cameroon. system utilizes Genetic Algorithm (GA) Backstepping Controller (BSC) methodologies. dynamically adjusts duty cycle Single Ended Primary Inductor Converter (SEPIC) align with reference voltage Maroua's dynamic environment. environment, characterized intermittent sunlight impact local factors shadowing, affects production energy. employed enhance BSC gains optimization technique expedites process minimizes oscillations GMPP. adaptability learning algorithm specific improves energy generation, even challenging environment Maroua. novel Cameroon, tailoring them dynamics region. In terms our surpasses INC-BSC, P&O-BSC, GA-BSC, PSO-BSC practice, stabilization period following typically requires fewer than three iterations. Additionally, Tracking (MPPT) technology based on methodology, contrasting alternative technologies that prioritize Local (LMPP). differentiation relevant areas shading, such as where use LMPP-based can result losses. proposed method demonstrates significant performance achieving minimum 33% reduction

Язык: Английский

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Natural resource‐driven prosperity: Unveiling the catalysts of sustainable economic development in the United States

Natural Resources Forum, Год журнала: 2024, Номер unknown

Опубликована: Апрель 5, 2024

Abstract Achieving economic progress hinges upon the active and strategic utilization of a nation's inherent resources in financial endeavors. This comprehensive study investigates intricate dynamics influencing development United States, employing time series dataset spanning from 1991 to 2022. Key factors including total natural resource rents, domestic capital formation, ‘financial risk index (FRI),’ count patents filed by both foreign investors. Rigorous statistical analyses, ‘Modified Dickey‐Fuller’ test ‘Bayer‐Hanck cointegration’ strategy, were employed extract meaningful insights data. Addressing concerns related endogeneity serial correlation, advanced techniques such as ‘Dynamic Ordinary Least Squares’ ‘Fully Modified applied. The findings illuminate pivotal roles played rents formation propelling sustainable States. Notably, this sheds light on positive contributions patent filings trajectory. Furthermore, enhancements FRI are identified catalysts for fostering growth. In essence, our research contributes existing body knowledge offering nuanced into multifaceted influences shaping landscape results not only underscore significance effective management but also emphasize impact innovation, represented filings, improvements journey towards

Язык: Английский

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Determinants of the transition towards circular economy in SMEs: a sustainable supply chain management perspective

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(11), С. 16865 - 16883

Опубликована: Фев. 7, 2024

Язык: Английский

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Unlocking the potential of blockchain technology in enhancing the fisheries supply chain: an exploration of critical adoption barriers in China

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Май 3, 2024

The application of blockchain technology holds significant potential for improving efficiency, resilience, and transparency within the Fisheries Supply Chain (FSC). This study addresses critical barriers hindering adoption (BT) in Chinese FSC, recognizing unique challenges posed by its intricacies. Through a comprehensive literature review, fourteen Critical Barrier Factors (CBFs) were identified, grey Delphi method was employed to distill this set. Five pivotal CBFs emerged, including "Regulatory Compliance," "Cost Implementation," "Complex Network". A subsequent Decision-Making Trial Evaluation Laboratory (DEMATEL) analysis revealed causal relationships among these factors, categorizing them into effect cause groups. Network" identified as primary influencing factors demanding attention effective BT integration FSC. findings serve valuable resource FSC stakeholders, assisting prioritizing efforts address barriers. discerned provide guidance managers optimizing allocation. Ultimately, research advocates fisheries supply chain enhance overall performance operational efficiency.

Язык: Английский

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