Optimal Sizing and Energy Management for Cost-Effective PEV Hybrid Energy Storage Systems

2020 ◽  
Vol 16 (5) ◽  
pp. 3407-3416 ◽  
Author(s):  
Xiaoying Lu ◽  
Haoyu Wang
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Storage Systems ◽  
Cost Effective ◽  
Energy Storage Systems ◽  
Optimal Sizing ◽  
Hybrid Energy ◽  
Hybrid Energy Storage

scholarly journals Optimal Energy Management of Railroad Electrical Systems with Renewable Energy and Energy Storage Systems

2019 ◽  
Vol 11 (22) ◽  
pp. 6293 ◽  
Author(s):  
Seunghyun Park ◽  
Surender Reddy Salkuti
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Energy Management ◽  
Storage Systems ◽  
Solar Pv ◽  
Energy Storage Systems ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Optimal Energy ◽  
Optimal Energy Management

The proposed optimal energy management system balances the energy flows among the energy consumption by accelerating trains, energy production from decelerating trains, energy from wind and solar photovoltaic (PV) energy systems, energy storage systems, and the energy exchange with a traditional electrical grid. In this paper, an AC optimal power flow (AC-OPF) problem is formulated by optimizing the total cost of operation of a railroad electrical system. The railroad system considered in this paper is composed of renewable energy resources such as wind and solar PV systems, regenerative braking capabilities, and hybrid energy storage systems. The hybrid energy storage systems include storage batteries and supercapacitors. The uncertainties associated with wind and solar PV powers are handled using probability distribution functions. The proposed optimization problem is solved using the differential evolution algorithm (DEA). The simulation results show the suitability and effectiveness of proposed approach.

scholarly journals Development of Machine Learning Methods in Hybrid Energy Storage Systems in Electric Vehicles

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Tzu-Chia Chen ◽  
Fouad Jameel Ibrahim Alazzawi ◽  
John William Grimaldo Guerrero ◽  
Paitoon Chetthamrongchai ◽  
Aleksei Dorofeev ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Storage ◽  
Energy Management ◽  
Management System ◽  
Storage Systems ◽  
Energy Management System ◽  
Energy Storage Systems ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Machine Learning Methods

The hybrid energy storage systems are a practical tool to solve the issues in single energy storage systems in terms of specific power supply and high specific energy. These systems are especially applicable in electric and hybrid vehicles. Applying a dynamic and coherent strategy plays a key role in managing a hybrid energy storage system. The data obtained while driving and information collected from energy storage systems can be used to analyze the performance of the provided energy management method. Most existing energy management models follow predetermined rules that are unsuitable for vehicles moving in different modes and conditions. Therefore, it is so advantageous to provide an energy management system that can learn from the environment and the driving cycle and send the needed data to a control system for optimal management. In this research, the machine learning method and its application in increasing the efficiency of a hybrid energy storage management system are applied. In this regard, the energy management system is designed based on machine learning methods so that the system can learn to take the necessary actions in different situations directly and without the use of predicted select and run the predefined rules. The advantage of this method is accurate and effective control with high efficiency through direct interaction with the environment around the system. The numerical results show that the proposed machine learning method can achieve the least mean square error in all strategies.

Sign in / Sign up

Export Citation Format

Share Document