Peak Demand Cutting Strategy with an On-Board Energy Storage System in Mass Rapid Transit

2018 ◽  
Vol 42 (1) ◽  
pp. 49-62 ◽  
Author(s):  
Chaiyut Sumpavakup ◽  
Sujin Suwannakijborihan ◽  
Tosaphol Ratniyomchai ◽  
Thanatchai Kulworawanichpong
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Rapid Transit ◽  
Peak Demand ◽  
Cutting Strategy ◽  
Mass Rapid Transit

scholarly journals Battery energy storage system (BESS) design for peak demand reduction, energy arbitrage and grid ancillary services

2020 ◽  
Vol 11 (1) ◽  
pp. 398
Author(s):  
Wan Syakirah Wan Abdullah ◽  
Miszaina Osman ◽  
Mohd Zainal Abidin Ab Kadir ◽  
Renuga Verayiah
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
Storage System ◽  
Energy Storage System ◽  
Battery Energy Storage System ◽  
Peak Demand ◽  
Battery Energy Storage ◽  
Demand Reduction ◽  
The Stability ◽  
Battery Energy

<span style="font-size: 9pt; font-family: 'Times New Roman', serif;">Renewable Energy (RE) penetration is a new phenomenon in power systems. In the advent of high penetration of RE in the systems, several issues have to be addressed especially when it involves the stability and flexibility of the power systems. Battery Energy Storage System (BESS) has gained popularity due to its capability to store energy and to serve multiple purposes in solving various power system concerns. Additionally, several BESS can be combined to operate as Virtual Power Plant (VPP). This study will involve the design and implementation of BESS for five potential customer sites for the demonstration project and to be possibly integrated into one VPP system. The study is expected to demonstrate bill savings to the customers with BESS due to peak demand reduction and energy arbitrage savings.</span><table class="MsoNormalTable" style="width: 444.85pt; border-collapse: collapse; border: none; mso-border-alt: solid windowtext .5pt; mso-yfti-tbllook: 1184; mso-padding-alt: 0in 5.4pt 0in 5.4pt; mso-border-insideh: .5pt solid windowtext; mso-border-insidev: .5pt solid windowtext;" width="593" border="1" cellspacing="0" cellpadding="0"><tbody><tr style="mso-yfti-irow: 0; mso-yfti-firstrow: yes; mso-yfti-lastrow: yes; height: 63.4pt;"><td style="width: 290.6pt; border: none; border-top: solid windowtext 1.0pt; mso-border-top-alt: solid windowtext .5pt; padding: 0in 5.4pt 0in 5.4pt; height: 63.4pt;" valign="top" width="387"><p class="MsoNormal" style="margin-top: 6.0pt; text-align: justify;"><span style="font-size: 9.0pt; color: black; mso-bidi-font-style: italic;">Renewable Energy (RE) penetration is a new phenomenon in power systems. In the advent of high penetration of RE in the systems, several issues have to be addressed especially when it involves the stability and flexibility of the power systems. Battery Energy Storage System (BESS) has gained popularity due to its capability to store energy and to serve multiple purposes in solving various power system concerns. Additionally, several BESS can be combined to operate as Virtual Power Plant (VPP). This study will involve the design and implementation of BESS for five potential customer sites for the demonstration project and to be possibly integrated into one VPP system. The study is expected to demonstrate bill savings to the customers with BESS due to peak demand reduction and energy arbitrage savings.</span></p></td></tr></tbody></table>

Energy storage system for peak shaving

2016 ◽  
Vol 10 (1) ◽  
pp. 3-18 ◽  
Author(s):  
Kein Huat Chua ◽  
Yun Seng Lim ◽  
Stella Morris
Keyword(s):  
Adaptive Control ◽  
Energy Storage ◽  
Control Algorithm ◽  
Storage System ◽  
Threshold Level ◽  
Energy Storage System ◽  
Peak Demand ◽  
Peak Shaving ◽  
Content Type ◽  
Adaptive Control Algorithm

Purpose – The main purpose of this study is to provide an effective sizing method and an optimal peak shaving strategy for an energy storage system to reduce the electrical peak demand of the customers. A cost-savings analytical tool is developed to provide a quick rule-of-thumb for customers to choose an appropriate size of energy storage for various tariff schemes. Design/methodology/approach – A novel sizing method is proposed to obtain the optimum size of energy storage for commercial and industrial customers based on their historical load profile. An algorithm is developed to determine the threshold level for peak shaving. One of the buildings at Universiti Tunku Abdul Rahman (UTAR), Malaysia, is chosen for this study. A three-phase energy storage system rated at 15 kVA is developed and connected to the low-voltage electrical network in the building. An adaptive control algorithm is developed and implemented to optimize the peak shaving. Findings – The sizing analysis shows that the customer under the C2 tariff rate yields the highest saving, followed by E2, C1 and E1. The experimental results presented indicate that the proposed adaptive control algorithm has effectively optimized the peak demand to be shaved. Research limitations/implications – This study demonstrates the potential of energy storage in reducing the peak demand and cost of electricity. One of the main challenges of real-time peak shaving is to determine an appropriate threshold level such that the energy stored in the energy storage system is sufficient during the peak shaving process. Originality/value – The originality of the paper is the optimal sizing method of the energy storage system based on the historical load profile and adaptive control algorithm to optimize the peak demand deduction.

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