scholarly journals A Fuzzy-Logic Power Management Strategy Based on Markov Random Prediction for Hybrid Energy Storage Systems

Energies ◽  
2016 ◽  
Vol 9 (1) ◽  
pp. 25 ◽  
Author(s):  
Yanzi Wang ◽  
Weida Wang ◽  
Yulong Zhao ◽  
Lei Yang ◽  
Wenjun Chen
Keyword(s):  
Fuzzy Logic ◽  
Energy Storage ◽  
Power Management ◽  
Management Strategy ◽  
Storage Systems ◽  
Energy Storage Systems ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Power Management Strategy ◽  
Markov Random

scholarly journals Power Management Control Strategy Based on Artificial Neural Networks for Standalone PV Applications with a Hybrid Energy Storage System

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 902 ◽  
Author(s):  
João Faria ◽  
José Pombo ◽  
Maria Calado ◽  
Sílvio Mariano
Keyword(s):  
Energy Storage ◽  
Power Management ◽  
Management Strategy ◽  
Storage Systems ◽  
Li Ion Batteries ◽  
Pv System ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Power Management Strategy ◽  
Li Ion

Standalone microgrids with photovoltaic (PV) solutions could be a promising solution for powering up off-grid communities. However, this type of application requires the use of energy storage systems (ESS) to manage the intermittency of PV production. The most commonly used ESSs are lithium-ion batteries (Li-ion), but this technology has a low lifespan, mostly caused by the imposed stress. To reduce the stress on Li-ion batteries and extend their lifespan, hybrid energy storage systems (HESS) began to emerge. Although the utilization of HESSs has demonstrated great potential to make up for the limitations of Li-ion batteries, a proper power management strategy is key to achieving the HESS objectives and ensuring a harmonized system operation. This paper proposes a novel power management strategy based on an artificial neural network for a standalone PV system with Li-ion batteries and super-capacitors (SC) HESS. A typical standalone PV system is used to demonstrate and validate the performance of the proposed power management strategy. To demonstrate its effectiveness, computational simulations with short and long duration were performed. The results show a minimization in Li-ion battery dynamic stress and peak current, leading to an increased lifespan of Li-ion batteries. Moreover, the proposed power management strategy increases the level of SC utilization in comparison with other well-established strategies in the literature.

Fuzzy logic based power management strategy using topographic data for an electric vehicle with a battery-ultracapacitor energy storage

2015 ◽  
Vol 34 (1) ◽  
pp. 173-188 ◽  
Author(s):  
Marek Michalczuk ◽  
Bartlomiej Ufnalski ◽  
Lech M. Grzesiak
Keyword(s):  
Energy Source ◽  
Fuzzy Logic ◽  
Energy Storage ◽  
Electric Vehicle ◽  
Power Management ◽  
Management Strategy ◽  
Content Type ◽  
Hybrid Energy ◽  
Management Algorithm ◽  
Power Management Strategy

Purpose – The purpose of this paper is to provide high-efficiency and high-power hybrid energy source for an urban electric vehicle. A power management strategy based on fuzzy logic has been introduced for battery-ultracapacitor (UC) energy storage. Design/methodology/approach – The paper describes the design and construction of on-board hybrid source. The proposed energy storage system consists of battery, UCs and two DC/DC interleaved converters interfacing both storages. A fuzzy-logic controller (FLC) for the hybrid energy source is developed and discussed. Control structure has been tested using a non-mobile experimental setup. Findings – The hybrid energy storage ensures high-power ability. Flexibility and robustness offered by the FLC give an easy accessible method to provide a power management algorithm extended with additional input information from road infrastructure or other vehicles. In the presented research, it was examined that using information related to the topography of the road in the control structure helps to improve hybrid storage performance. Research limitations/implications – The proposed control algorithm is about to be validated also in an experimental car. Originality/value – Exploratory studies have been provided to investigate the benefits of energy storage hybridization for electric vehicle. Simulation and experimental results confirm that the combination of lithium batteries and UCs improves performance and reliability of the energy source. To reduce power impulses drawn from the battery, power management algorithm takes into consideration information on slope of a terrain.

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