271 research outputs found

    A fast and accurate global maximum power point tracking controller for photovoltaic systems under complex partial shadings

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    The operating conditions of partially shaded photovoltaic (PV) generators created a need to develop highly efficient global maximum power point tracking (GMPPT) methods to increase the PV system performance. This paper proposes a simple, efficient, and fast GMPPT based on fuzzy logic control to reach the point of global maximum power. The approach measures the PV generator current in the areas where it is almost constant to estimate the local maximums powers and extracts the highest among them. The performance of this method is evaluated firstly by simulation versus four well-known recent methods, namely the hybrid particle swarm optimization, modified cuckoo search, scrutinization fast algorithm, and shade-tolerant maximum power point tracking (MPPT) based on current-mode control. Then, experimental verification is conducted to verify the simulation findings. The results confirm that the proposed method exhibits high performance for complex partial irradiances and can be implemented in low-cost calculators

    Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

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    The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

    Online parameters estimation schemes to enhance control performance in DC microgrids

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    This is the final version. Available on open access from Elsevier via the DOI in this recordThis paper addresses the problem of achieving current sharing and voltage balancing in DC microgrids when the filter parasitic resistances of the Distributed Generation Units (DGUs) are unknown and potentially time-varying. Two schemes are proposed for current sharing and voltage balancing, which use only generated current and voltage measurements. The first scheme is a novel distributed adaptive control utilising the principles of back-stepping and passivity-based control design, intended for the case of constant parasitic resistances. The second scheme alters an existing stabilising controller for current sharing and voltage balancing by incorporating the estimation of the unknown, possibly time-varying, parasitic resistance. A Super-Twisting Sliding Mode Algorithm (STA) estimates the parasitic resistance and its bounded variations in finite-time. The simulation results using a DC microgrid composed of 4 DGUs demonstrate the performance of the proposed schemes.Dutch Research Council (NWO)European Union Horizon 2020Innovate U

    Advances in Batteries, Battery Modeling, Battery Management System, Battery Thermal Management, SOC, SOH, and Charge/Discharge Characteristics in EV Applications

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    The second-generation hybrid and Electric Vehicles are currently leading the paradigm shift in the automobile industry, replacing conventional diesel and gasoline-powered vehicles. The Battery Management System is crucial in these electric vehicles and also essential for renewable energy storage systems. This review paper focuses on batteries and addresses concerns, difficulties, and solutions associated with them. It explores key technologies of Battery Management System, including battery modeling, state estimation, and battery charging. A thorough analysis of numerous battery models, including electric, thermal, and electro-thermal models, is provided in the article. Additionally, it surveys battery state estimations for a charge and health. Furthermore, the different battery charging approaches and optimization methods are discussed. The Battery Management System performs a wide range of tasks, including as monitoring voltage and current, estimating charge and discharge, equalizing and protecting the battery, managing temperature conditions, and managing battery data. It also looks at various cell balancing circuit types, current and voltage stressors, control reliability, power loss, efficiency, as well as their advantages and disadvantages. The paper also discusses research gaps in battery management systems.publishedVersio

    A review of commercialisation mechanisms for carbon dioxide removal

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    The deployment of carbon dioxide removal (CDR) needs to be scaled up to achieve net zero emission pledges. In this paper we survey the policy mechanisms currently in place globally to incentivise CDR, together with an estimate of what different mechanisms are paying per tonne of CDR, and how those costs are currently distributed. Incentive structures are grouped into three structures, market-based, public procurement, and fiscal mechanisms. We find the majority of mechanisms currently in operation are underresourced and pay too little to enable a portfolio of CDR that could support achievement of net zero. The majority of mechanisms are concentrated in market-based and fiscal structures, specifically carbon markets and subsidies. While not primarily motivated by CDR, mechanisms tend to support established afforestation and soil carbon sequestration methods. Mechanisms for geological CDR remain largely underdeveloped relative to the requirements of modelled net zero scenarios. Commercialisation pathways for CDR require suitable policies and markets throughout the projects development cycle. Discussion and investment in CDR has tended to focus on technology development. Our findings suggest that an equal or greater emphasis on policy innovation may be required if future requirements for CDR are to be met. This study can further support research and policy on the identification of incentive gaps and realistic potential for CDR globally

    Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021

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    The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on the Energy Internet, blockchain technology and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

    Advanced Modeling and Research in Hybrid Microgrid Control and Optimization

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    This book presents the latest solutions in fuel cell (FC) and renewable energy implementation in mobile and stationary applications. The implementation of advanced energy management and optimization strategies are detailed for fuel cell and renewable microgrids, and for the multi-FC stack architecture of FC/electric vehicles to enhance the reliability of these systems and to reduce the costs related to energy production and maintenance. Cyber-security methods based on blockchain technology to increase the resilience of FC renewable hybrid microgrids are also presented. Therefore, this book is for all readers interested in these challenging directions of research

    Power System Digital Twins and Real-Time Simulations in Modern Grids

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    Power systems are in a state of constant change with new hardware, software and applications affecting their planning, operation, and maintenance. Power system control centers are also evolving through new technologies and functionalities to adapt to current needs. System control rooms have moved from fully manual to automated operations, from analog to digital, and have become an embedded and complex information, communication, computation and control system. Digital twins are virtual representations of physical systems, assets and/or processes. They are enabled through software, hardware and data integration, and allow real-time monitoring, controlling, prediction, optimization, and improved decision-making. Consequently, digital twins arise as a technology capable of incorporating existing control systems along with new ones to collect, classify, store, retrieve and disseminate data for the future generation of control centers. Power system digital twins (PSDTs) can uplift how data from power grids and their equipment is processed, providing operators new ways to visualize and understand the information. Nevertheless, complexity and size of modern power systems narrow the scope a current digital twin can have. Furthermore, the services provided are limited to only certain phenomena and/or applications. This thesis addresses the need for a flexible and versatile solution that is also robust and adaptable for monitoring, operating and planning future power systems. The modular design for implementation of the next generation of PSDTs is proposed based on grid applications and/or services they can provide. From a modeling perspective, this thesis also distinguishes how real-time simulations enable the design, development, and operation of a PSDT. First, the need for enhanced power system modeling and simulation techniques is established. Moreover, the necessity of expanding to a more complete and varied open-source library of power system models is identified. The thesis continues by designing, developing, and testing models of inverter-based resources that can be used by the industry and researchers when developing PSDTs. Furthermore, the first-of-its-kind synthetic grid with a longitudinal structure, the S-NEM2300-bus benchmark model, based on the Australian National Electricity Market is created. The synthetic grid is, finally, used to illustrate the first steps towards implementing a practical PSDT

    Reliability Enhancing Control Algorithms for Two-Stage Grid-Tied Inverters

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    In the photovoltaic (PV) generation system, two types of grid-tied inverter systems are usually deployed: the single-stage grid-tied inverter system and the two-stage grid-tied inverter system. In the single-stage grid-tied inverter system, the input of the inverter is directly connected to the PV arrays, while an additional dc-dc stage is inserted between the PV arrays and the dc-ac inverter in the two-stage design. The additional dc-dc stage could provide a stable dc-link voltage to the inverter, which also enables new design possibilities, including the multi-MPPT operation and solar-plus-storage application. Thus, the two-stage grid-tied inverter has been widely used in the PV generation system.As the core component of the PV generation system, the reliability of the grid-tied inverter determines the overall robustness of the system. The two-stage grid-tied inverter system includes three parts: the dc-dc stage, dc-link capacitor, and dc-ac inverter. Thus, the reliability of the two-stage grid-tied inverter relies on the reliability of each part. The dc-dc stage is used to provide a stable dc-link voltage to the inverter. However, when the inverter stage provides constant power to the grid, the load of the dc-dc stage becomes the constant power load (CPL), which will deteriorate the stability of the dc-dc stage. The dc-link capacitor is used to attenuate the voltage ripple on the dc-link and balance the transient power mismatch between the dc-dc stage and the dc-ac stage. However, during the operation of the inverter system, the degradation of the capacitor will reduce the converter reliability, and even result in system failure. The inverter stage is connected to the grid through the output filter, and the LCL type filter has been commonly used due to its superior performance. The resonance of the LCL filter must be properly damped to enhance the inverter stability. However, the grid-side impedance will lead to the resonant frequency drifting of the LCL filter, which will worsen the stability margin of the inverter. Thus, the control design of the two-stage grid-tied inverter system must consider those reliability challenges. In this work, three control algorithms are proposed to solve the reliability challenges. For the dc-dc stage, an uncertainty and disturbance estimator (UDE) based robust voltage control scheme is proposed. The proposed voltage control scheme can actively estimate and compensate for the disturbance of the dc-dc stage. Both the disturbance rejection performance and the stability margin of the dc-dc stage, especially under the CPL, could be enhanced. For the dc-link capacitor, a high-frequency (HF) signal injection based capacitance estimation scheme is proposed. The proposed estimation scheme can monitor the actual dc-link capacitance in real-time. For the inverter stage, an adaptive extremum seeking control (AESC) based LCL filter resonant frequency estimation scheme is proposed. The AESC-based estimation scheme can estimate the resonant frequency of the LCL filter online. All the proposed reliability enhancing control algorithms could enhance the reliability of the two-stage grid-tied inverter system. Detailed theoretical analysis, simulation studies, and comprehensive experimental studies have been performed to validate the effectiveness
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