scholarly journals Accuracy improvement of SOC estimation in lithium-ion batteries by ANFIS vs ANN modeling of nonlinear cell characteristics

2021 ◽  
Author(s):  
Mohammad Hassan Amir Jamlouie
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Intelligent System ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Training Data ◽  
Accurate Estimation ◽  
Consumption Pattern ◽  
Load Prediction

Over the last century, the energy storage industry has continued to evolve and adapt to changing energy requirements. To run an efficient energy storage system two points must be considered. Firstly, precise load forecasting to determine energy consumption pattern. Secondly, is the correct estimation of state of charge (SOC). In this project there is a model introduced to predict the load consumption based on ANN implemented by MATLAB. The Designed intelligent system introduced for load prediction according to the hypothetical training data related to two years daily based load consumption of a residential area. For another obstacle which is accurate estimation of SOC, two separate models are provided based on ANN and ANFIS for Lithium-ion batteries as an energy storage system. There are several researches in this regard but in this project the author makes an effort to introduce the most efficient based on the MSE of each performance and as a result the method by ANN is found more accurate.

scholarly journals Accuracy improvement of SOC estimation in lithium-ion batteries by ANFIS vs ANN modeling of nonlinear cell characteristics

2021 ◽  
Author(s):  
Mohammad Hassan Amir Jamlouie
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Intelligent System ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Training Data ◽  
Accurate Estimation ◽  
Consumption Pattern ◽  
Load Prediction

Over the last century, the energy storage industry has continued to evolve and adapt to changing energy requirements. To run an efficient energy storage system two points must be considered. Firstly, precise load forecasting to determine energy consumption pattern. Secondly, is the correct estimation of state of charge (SOC). In this project there is a model introduced to predict the load consumption based on ANN implemented by MATLAB. The Designed intelligent system introduced for load prediction according to the hypothetical training data related to two years daily based load consumption of a residential area. For another obstacle which is accurate estimation of SOC, two separate models are provided based on ANN and ANFIS for Lithium-ion batteries as an energy storage system. There are several researches in this regard but in this project the author makes an effort to introduce the most efficient based on the MSE of each performance and as a result the method by ANN is found more accurate.

scholarly journals Economic analysis for centralized battery energy storage system with reused battery from EV in Australia

2021 ◽  
Vol 300 ◽  
pp. 01003
Author(s):  
Yunfan Meng
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Economic Model ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Development Potential ◽  
Battery Energy

With battery energy storage technology development, the centralized battery energy storage system (CBESS) has a broad prospect in developing electricity. In the meantime, the retired lithium-ion batteries from electric vehicles (EV) offer a new option for battery energy storage systems (BESS). This paper studies the centralized reused battery energy storage system (CRBESS) in South Australia by replacing the new lithium-ion batteries with lithium-ion second-life batteries (SLB) and evaluating the economic benefits with economic indicators as net present value (NPV), discounted payback period (DPBP), Internal rate of return (IRR) to depict a comprehensive understanding of the development potential of the CRBESS with the lithium-ion SLB as the energy storage system. This paper proposes a calculation method of frequency control ancillary services (FCAS) revenue referring to market share rate (MSR) when building the economic model. Moreover, the residual value of lithium-ion batteries is considered. This paper uses the economic model to calculate the profitability and development potential of CRBESS. From an economic perspective, the superiority and feasibility of CRBESS compared with CBESS were analyzed.

scholarly journals SOC Estimation of Lithium-Ion Battery Based on Kalman Filter Algorithm for Energy Storage System in Microgrids

2018 ◽  
Vol 57 ◽  
pp. 02006 ◽  
Author(s):  
Dae-Won Chung ◽  
Seung-Hak Yang
Keyword(s):  
Kalman Filter ◽  
Energy Storage ◽  
Power Systems ◽  
Lithium Ion Battery ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Accurate Estimation ◽  
Soc Estimation ◽  
Internal States

State-of-charge (SOC) is one of the vital factors for the energy storage system (ESS) in the microgrid power systems to guarantee that a battery system is operating in a safe and reliable manner for the system. Many uncertainties and noises, such as nonlinearities in the internal states of a battery, sensor measurement accuracy and bias, temperature effects, calibration errors, and sensor failures, pose a challenge to the accurate estimation of SOC in most applications. This study makes two contributions to the existing literatures. First, a more accurate extended Kalman filter (EKF) algorithm is proposed to estimate the battery nonlinear dynamics. Due to its discrete form and ease of implementation, this straightforward approach could be more suitable for real applications on the ESS. Second, its order selection principle and parameter identification method are illustrated in detail. It can accurately demonstrate the characteristics of the lithium-ion battery to show the feasibility and effectiveness of the algorithm for the ESS.

scholarly journals Economic Feasibility of Echelon Utilization Battery in Photovoltaic Energy Storage

2020 ◽  
Vol 194 ◽  
pp. 02001
Author(s):  
Yibin Tao ◽  
Jinhua Xue ◽  
Min Xia ◽  
Jin Tao ◽  
Qichao Zhang ◽  
...  
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Lithium Ion Battery ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Economic Feasibility ◽  
Photovoltaic Energy ◽  
Power Load ◽  
Whole Life Cycle

Taking the power load of an industrial park in Shanghai as an example in this paper, particle swarm optimization and cost-benefit model are employed to analyse the economy of new lithium-ion batteries, echelon lithium-ion batteries and lead-carbon batteries in photovoltaic energy storage systems in the whole life cycle. The research results showed that the economic order from large to small among different batteries in the photovoltaic energy storage system was new lithium-ion battery, echelon utilization lithium-ion battery and lead-carbon battery. The declines in energy storage cost and discount rate and the rise in peak electricity price can greatly improve the net present value of a photovoltaic-energy storage system (PV-BES) system.

A High-Performance Lithiated Silicon-Sulfur Battery Enabled by Fluorinated Ether Electrolytes

2021 ◽  
Author(s):  
Leicheng Zhang ◽  
Chen ZHAO ◽  
Yanke Lin ◽  
Maochun Wu ◽  
T. S. Zhao
Keyword(s):  
Energy Storage ◽  
Energy Density ◽  
Lithium Ion Batteries ◽  
High Performance ◽  
Lower Cost ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Sulfur Battery ◽  
Fluorinated Ether

Lithiated silicon-sulfur (Si-S) batteries are an attractive energy storage system that can offer higher theoretical energy density and lower cost than current lithium-ion batteries. However, this type of battery using...

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