Charge migration efficiency optimization in hybrid electrical energy storage (HEES) systems

Wang, Hong; Kim, Younghyun; Xie, Weibo; Chang,; Pedram,

doi:10.1109/islped.2011.5993620

Cited by 47 publications

(47 citation statements)

References 10 publications

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“…The system models two battery banks, a PV module and the bidirectional CTI bus, managed by a dedicated controller, not shown, as presented in [38]. Each unit is connected to the CTI by means of a bidirectional DC-DC converter for level shifting and charge routing, while the PV's one is unidirectional.…”

Section: The System Modeling Frameworkmentioning

confidence: 99%

Joint Computing and Electric Systems Optimization for Green Datacenters

Pahlevan

Rossi

Valle

et al. 2016

Handbook of Hardware/Software Codesign

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This chapter presents an optimization framework to manage green datacenters using multi-level energy reduction techniques in a joint approach. A green datacenter exploits renewable energy sources and active Uninterruptible Power Supply (UPS) units to reduce the energy intake from the grid while improving its Quality of Service (QoS). At server level, the state-of-the-art correlation-aware Virtual Machines (VMs) consolidation technique allows to maximize server's energy efficiency. At system level, heterogeneous Energy Storage Systems (ESS) replace standard UPSs while a dedicated optimization strategy aims at maximizing the lifetime of the battery banks and to reduce the energy bill, considering the load of the servers. Results demonstrate, under different number of VMs in the system, up to 11.6% energy savings, 10.4% improvement of QoS compared to existing correlation-aware VM allocation schemes for datacenters and up to 96% electricity bill savings. IntroductionEver increasing demands for computing and growing number of clusters and servers in datacenters have ramped up the power consumption costs as an undesirable effect [21]. On the other hand, traditional fossil fuel concerns, carbon emissions and global warming impose the introduction of more sustainable energy sources and behavioural change of people [41], since 10% of the global consumption of electrical energy has been estimated to be consumed by Information Technology (IT) infrastructures [14].

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Section: The System Modeling Frameworkmentioning

confidence: 99%

Joint Computing and Electric Systems Optimization for Green Datacenters

Pahlevan

Rossi

Valle

et al. 2016

Handbook of Hardware/Software Codesign

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“…The system controller adjusts the charger output current, thereby maintaining the operating point of the PV panel. The power consumption of the charger is a function of , , and [5]. Based on this model, we can calculate the charger output current as a function of , , and :…”

Section: B Charger Modelmentioning

confidence: 99%

Capital Cost-Aware Design and Partial Shading-Aware Architecture Optimization of a Reconfigurable Photovoltaic System

Wang¹,

Li²,

Pedram³

et al. 2013

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2013

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Abstract-Photovoltaic (PV) systems are often subject to partial shading that significantly degrades the output power of the whole systems. Reconfiguration methods have been proposed to adaptively change the PV panel configuration according to the current partial shading pattern. The reconfigurable PV panel architecture integrates every PV cell with three programmable switches to facilitate the PV panel reconfiguration. The additional switches, however, increase the capital cost of the PV system. In this paper, we group a number of PV cells into a PV macro-cell, and the PV panel reconfiguration only changes the connections between adjacent PV macro-cells. The size and internal structure (i.e., the series-parallel connection of PV cells) of all PV macro-cells are the same and will not be changed after PV system installation in the field. Determining the optimal size of the PV macro-cell is the result of a trade-off between the decreased PV system capital cost and enhanced PV system performance. A larger PV macro-cell reduces the cost overhead whereas a smaller PV macro-cell achieves better performance. In this paper, we set out to calculate the optimal size of the PV macro-cells such that the maximum system performance can be achieved subject to an overall system cost limitation. This "design" problem is solved using an efficient search algorithm. In addition, we provide for in-field reconfigurability of the PV panel by enabling formation of seriesconnected groups of parallel-connected macro-cells. We ensure maximum output power for the PV system in response to any incurring partial shading pattern. This "architecture optimization" problem is solved using dynamic programming.

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“…We obtain the V-I characteristics and MPP of a PV cell under any using the PV cell model of reference [10]. We adopt the battery and charger models from [11]. Generally speaking, the power conversion efficiency of a charger is a function of its input and output voltages and currents.…”

Section: Component Modelsmentioning

confidence: 99%

“…From the Kirchhoff's laws, we have: (4) , for and (5) and (6) We control and maintain the PV array operating point using the PV charger. The power loss of the PV charger, , is calculated from its input voltage, input current, output voltage, and output current, i.e., , , , and , respectively [11]. Due to the energy conservation law, we have: (7) where and are the battery's terminal voltage and charging current from the PV system, respectively.…”

Section: Problem Statementmentioning

confidence: 99%

Dynamic reconfiguration of photovoltaic energy harvesting system in hybrid electric vehicles

Wang

Lin

Chang

et al. 2012

Proceedings of the 2012 ACM/IEEE International Symposium on Low Power Electronics and Design

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Photovoltaic (PV) energy harvesting system is a promising energy source for battery replenishment in hybrid electric vehicles (HEVs.) The PV cell array is installed on different parts of a vehicle body such as the engine hood, door panels, and the roof panel. Non-uniformity of the solar irradiance and temperature on the PV cell array is, however, a serious obstacle to efficient utilization of the PV system in HEVs because such variation, if not managed properly, can result in a significant degradation in the overall output power level of the PV system. This paper presents a dynamic PV array reconfiguration technique with structural support and a dynamic programming-based algorithm with polynomial time complexity to produce the near-optimal reconfiguration of the PV array on the HEV. The goal of this technique is to maximize the PV system output power under any solar irradiance and temperature distribution on the PV array. We demonstrate up to 6X improvement in the output power of a PV system against a conventional fixed configuration PV system.

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Charge migration efficiency optimization in hybrid electrical energy storage (HEES) systems

Cited by 47 publications

References 10 publications

Joint Computing and Electric Systems Optimization for Green Datacenters

Joint Computing and Electric Systems Optimization for Green Datacenters

Capital Cost-Aware Design and Partial Shading-Aware Architecture Optimization of a Reconfigurable Photovoltaic System

Dynamic reconfiguration of photovoltaic energy harvesting system in hybrid electric vehicles

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