Determination of lead-acid battery capacity via mathematical modeling techniques

Casacca, M.A.; Salameh, Z.M.

doi:10.1109/60.148564

Cited by 88 publications

(24 citation statements)

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“…This effect appears in most battery models [1][2][3][4] mentioned in the literature. The discontinuity at this point has a simple solution: to allow linear battery voltage evolution at the change of operation mode.…”

Section: Saturationmentioning

confidence: 84%

“…Despite the fact that batteries are widely used, the behaviour of their electrochemical reactions hide an unexpected complexity. The problem of simulating lead-acid batteries by means of equivalent electrical circuits has been described in the literature, [1][2][3][4] and different models can be found to have different degrees of complexity and simulation quality. Some models offer a good compromise between complexity and precision, but the problem of modelling batteries for the analysis of photovoltaic systems using lead-acid batteries has not been satisfactorily solved yet.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic battery model for photovoltaic applications

Guasch

Silvestre

2003

Progress in Photovoltaics

110

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The main purpose of this paper is to offer a useful battery model for simulation of stand-alone photovoltaic applications. At present, many models for battery behaviour simulation are available. Owing to the complex response of this element, these models are mainly concerned with stationary working point conditions. This paper presents an enhancement of a generic battery model, achieving a dynamic battery model for photovoltaic applications. It includes the use of automatic parameter extraction techniques and the solving of numerical calculation problems. It also introduces some new concepts, such as the maximum available capacity and the level of energy. Finally, a battery state of health estimation, has been added to complete the battery behaviour description, including non-ideal effects, such as battery capacity reduction and self-discharging current.

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Section: Saturationmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Dynamic battery model for photovoltaic applications

Guasch

Silvestre

2003

Progress in Photovoltaics

110

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“…Bataryaların çalışma durumlarındaki SOC ve diğer parametrelerinin tahmin edilmesine yönelik literatürde çeşitli yöntemler denenmiştir. Kurşun asit aküler gibi ucuz ve yaygın akü türlerinin şarj durumlarının izlenmesi [1,2] özellikle telekomünikasyon tesisleri açısından önemli bir çalışma olarak yer almaktadır. Chiasson ve Vairamohan [3] tarafından gerçekleştirilen çalışmada ise elektrokimyasal piller için SOC nin şarj durumundaki değişiminin kestirimi araştırılmıştır.…”

Section: Introductionunclassified

Li̇tyum İon Bataryalarin Deşarj Durumu Davranişlarinin Geneti̇k İfade Programlama İle Kesti̇ri̇mi̇

Avgın¹,

Yılmaz²,

Ünsal³

2014

KSU J. Eng. Sci.

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ÖZET: Artış gösteren kişisel ve iş yaşamındaki enerji tüketimine bağlı olarak, batarya sektöründe daha gelişmiş teknolojilerin ortaya çıkmasına ihtiyaç duyulmaktadır. Bu noktada öncelikli olarak bir bataryadan beklenen, ihtiyaç duyulan enerjiyi, ihtiyaç duyulan zaman süresince sağlamasıdır. Bunun yanında şarj doluluk durumu bilgisinin doğru ve kesin olarak bilinmesi de batarya yönetim sisteminin en önemli unsurlarından biridir. Bu çalışmada, lityum-ion (Li-Ion) akü yönetim sisteminin en önemli unsurlarından birisi olan batarya doluluk durumunu için genetik ifade programlama algoritması ile kestirimi incelenmiştir. Kestirim çalışmasında giriş değerleri olarak atanan batarya akımı, batarya çıkış voltajı ve zaman değişkenleri ile çıkış değeri olarak batarya türlerine özel şarj doluluk durumu verileri elde edilmiştir. Lityum-İon aküler için matematiksel deşarj denklemleri oluşturulmuş ve böylece pil türüne özel deşarj bilgileriyle daha doğru ve kesin SOC tahmini yapılabilmesi amaçlanmıştır. Lithium-Ion Battery Discharge Status Of Genetic Expression Behavior And Prediction OfProgramming ABSTRACT: Due to continuous increase of energy consumption in personal and business life, the battery industry, the emergence of more advanced technologies are needed. In this respect, for a battery user, expected to be a priority, the energy needed, the duration of time needed to provide. However accurate and precise knowledge of the state-ofcharge is one of the most important components of a battery management system. In this study, estimation of battery state of charge parameter using genetic expression programming is investigated. To estimate the state-of-charge, which is the most important component of battery management system, estimation methods and battery models in the literature are summarized. In the simulation, the variables of battery current, battery terminal voltage and the time are assigned as inputs. With this process, new specific state-of-charge data and are mathematical discharge equations are obtained for each Lithium-Ion, battery types. Hence, it is intended to reach an accurate and precise state-of-charge estimation due to battery types.

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“…This model was developed using nonlinear elements and allows a continuous evaluation of battery performance [8,11]. The model components were found using manufacturing specifications and experimental tests.…”

Section: B Battery Equivalent Circuitsmentioning

confidence: 99%

Comparison of dynamic models of battery energy storage for frequency regulation in power system

Adrees

Andami

Milanović

2016

2016 18th Mediterranean Electrotechnical Conference (MELECON)

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Abstract-The paper investigates the use of frequently discussed battery energy storage system (BESS) models for frequency regulation studies. Integration of a large number of renewable generation sources results in increased uncertainty in electric power generation, requiring, among the others, more frequency regulation services than before. The battery energy storage system models are compared and evaluated to assess their suitability for frequency regulation studies. The accuracy and complexity of BES models reported in the past are also discussed. Index Terms-Battery energy storage systems, Load frequency control (LFC), Battery models I. INTRODUCTIONhe operation of an electric power system is a complex process of forecasting the demand for electricity, and scheduling and operating a large number of power plants to meet that varying demand in real time. At every instant, electrical power generation should match power consumption to keep system frequency constant.The integration of renewable energy sources reduces the dependence on fossil fuels and greenhouse gas emission but increases variability and uncertainty in electric power generation. It is estimated that for every 10% wind penetration, a balancing power from other generation sources equivalent to 2% to 4% of the installed wind capacity is required for a stable power system operation [1]. Thus, with more penetration of intermittent renewables, the power system operation will become more complex and will require additional balancing power. As a result of this, there have been serious concerns over the safe and reliable operation of power systems with large penetration of renewable sources and reduction in conventional generation.Effective energy storage can match total generation to total load precisely on a second by second basis. Energy storage can facilitate load leveling for generators, load leveling for postponement of grid upgrade, frequency regulation, and power quality. Conventional generators may take several minutes or even hours to come online and will consume fuel

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Determination of lead-acid battery capacity via mathematical modeling techniques

Cited by 88 publications

References 1 publication

Dynamic battery model for photovoltaic applications

Dynamic battery model for photovoltaic applications

Li̇tyum İon Bataryalarin Deşarj Durumu Davranişlarinin Geneti̇k İfade Programlama İle Kesti̇ri̇mi̇

Comparison of dynamic models of battery energy storage for frequency regulation in power system

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