Modeling of hybrid renewable energy systems

Deshmukh, M. K.; Deshmukh, Sandip

doi:10.1016/j.rser.2006.07.011

Cited by 735 publications

(297 citation statements)

References 84 publications

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“…The electricity generation process from wind is comprised of a wind turbine extracting a kinetic energy from the air flow. The wind is rarely steady; it is influenced by the weather system and the ground surface conditions, which are often turbulent [27]. Also, the generation process must happen at the same instant it is consumed unless it is stored in grid level battery banks.…”

Section: Frequency Stability In Wind-power Generationmentioning

confidence: 99%

“…Finally, the data were fit using smoothing splines 17 . The usable power generated from a wind turbine is generally described by a Rayleigh distribution [27]. It defines three main points in the wind power generation process: (1) the cut-in is the minimum viable wind speed for electricity generation from a wind turbine.…”

Section: Frequency Stability In Wind-power Generationmentioning

confidence: 99%

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Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

2017

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CLOUD COMPUTING COST AND ENERGY OPTIMIZATION THROUGH FEDERATED CLOUD SOSThe two most significant differentiators amongst contemporary Cloud Computing service providers have increased green energy use and datacenter resource utilization. This work addresses these two issues from a system's architectural optimization viewpoint. The proposed approach herein, allows multiple cloud providers to utilize their individual computing resources in three ways by:(1) cutting the number of datacenters needed, (2) scheduling available datacenter grid energy via aggregators to reduce costs and power outages, and lastly by (3) utilizing, where appropriate, more renewable and carbon-free energy sources. Altogether our proposed approach creates an alternative paradigm for a Federated Cloud SoS approach. The proposed paradigm employs a novel control methodology that is tuned to obtain both financial and environmental advantages. It also supports dynamic expansion and contraction of computing capabilities for handling sudden variations in service demand as well as for maximizing usage of time varying green energy supplies. Herein we analyze the core SoS requirements, concept synthesis, and functional architecture with an eye on avoiding inadvertent cascading conditions. We suggest a physical architecture that diminishes unwanted outcomes while encouraging desirable results. Finally, in our approach, the constituent cloud services retain their independent ownership, objectives, funding, and sustainability means.This work analyzes the core SoS requirements, concept synthesis, and functional architecture.It suggests a physical structure that simulates the primary SoS emergent behavior to diminish unwanted outcomes while encouraging desirable results. The report will analyze optimal computing generation methods, optimal energy utilization for computing generation as well as a procedure for building optimal datacenters using a unique hardware computing system design based on the openCompute community as an illustrative collaboration platform. Finally, the research concludes with ii security features cloud federation requires to support to protect its constituents, its constituents tenants and itself from security risks.iii ACKNOWLEDGEMENTS

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Section: Frequency Stability In Wind-power Generationmentioning

confidence: 99%

Section: Frequency Stability In Wind-power Generationmentioning

confidence: 99%

Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

2017

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“…For instance, research in electrochemical energy storage and supercapacitors investigates both material and efficiency related issues. Equipping product with local renewable energy sources is a hot topic of product engineering (Deshmukh and Deshmukh, 2008). Utilization of renewable energy sources and their integration has become a central theme of research in future energy systems (Liserre et al, 2010).…”

Section: Powering Of Technical Systemsmentioning

confidence: 99%

An initial categorization of foundational research in complex technical systems

Horváth

2015

J. Zhejiang Univ. Sci. A

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There has been intense foundational research in complex technical systems (CTSs) over the last half century. These systems are exemplified by advanced mechatronics systems, embedded control systems, real-time systems, agent-based smart systems, distributed software systems, internet of things systems, and cyber-physical systems. The objective of this paper is to offer an initial cataloguing of the various research domains and to identify the major research issues. The paper has an ontological flavour, because it concentrates on what research has been and is being done, rather than on why and how research is done. The underpinning study has been done in three stages: (i) intuition-driven exploration of a reference set of related academic publications, (ii) evidence-based specification of a categorization of the domains and subdomains of research, and (iii) refinement and validation of the proposed classification based on a control set of related academic publications. The proposed reasoning model identifies three categories of research domains. The 'intellectualizations' category includes research domains such as: (i) philosophy, (ii) ontology, and (iii) epistemology of CTSs. The research domains included in the 'realizations' category are: (iv) methodology, and (v) creation of CTSs. The domains considered in the 'influences' category are: (vi) manifestations, and (vii) axiology of CTSs. Based on the proposed reasoning model a landscape of foundational research in CTSs is proposed for public debate. Our follow-up study focuses on the extension of the proposed classification to other families of complex engineered systems such as sociotechnical systems and social ecosystems.

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“…A PV cell is a P-N junction that is typically modeled with an equivalent electrical circuit [8]. Although there are prior researches focused on non-electrical models based on either artificial neural network (ANN) [9] or adaptive neuro-fuzzy inference scheme (ANFIS) [10], the equivalent electrical circuit is the most popular PV model.…”

Section: Introductionmentioning

confidence: 99%

An accurate method for the PV model identification based on a genetic algorithm and the interior-point method

2014

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Citation: Dizqah, Arash, Maheri, Alireza and Busawon, Krishna (2014) Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) An Accurate Method for the PV Model Identification Based on a GeneticAlgorithm and the Interior-Point Method AbstractDue to the PV module simulation requirements as well as recent applications of model-based controllers, the accurate photovoltaic (PV) model identification method is becoming essential to reduce the PV power losses effectively. The classical PV model identification methods use the manufacturers provided maximum power point (MPP) at the standard test condition (STC). However, the nominal operating cell temperature (NOCT) is the more practical condition and it is shown that the extracted model is not well suited to it. The proposed method in this paper estimates an accurate equivalent electrical circuit for the PV modules using both the STC and NOCT information provided by the manufacturers. A multi-objective global optimization problem is formulated using only the main equation of the PV module at these two conditions that restrains the errors due to employing the experimental temperature coefficients. A novel combination of a genetic algorithm (GA) and the interior-point method (IPM) allows the proposed method to be fast and accurate regardless the PV technology. It is shown that the overall error, which is defined by the sum of the MPP errors of both the STC and the NOCT conditions, is improved by a factor between 5.1% to 31% depending on the PV technology.

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Modeling of hybrid renewable energy systems

Cited by 735 publications

References 84 publications

Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

An initial categorization of foundational research in complex technical systems

An accurate method for the PV model identification based on a genetic algorithm and the interior-point method

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