1
Return

Impact of Operational Decisions and Size of Battery Energy Storage Systems on Demand Charge Reduction

delete2019-06-01
delete13
PRE
AI
R
Roozbeh Karandeh *
T
Tumininu Lawanson
V
Valentina Cecchi
DOI:10.1109/ptc.2019.8810754delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Demand charge reduction is an influential application of BESS for distribution system utilities as well as microgrid operators that could be achieved through peak-shaving techniques. This paper studies the impact of the size of BESS and the BESS operational decisions including the initial state of charge (SoC) of a day, on peak-shaving. A linear programming-based algorithm is used for optimal energy management of BESS interfaced with Distributed Energy Resources (DERs) to determine the output power of the BESS for peak-shaving and demand charge reduction on each day. The problem is solved using MATLAB and implemented on a real-world distribution feeder modeled in OpenDSS, using predicted day-ahead demand and solar photovoltaic (PV) generation output. The results show that the BESS rated capacity is a more decisive factor than inverter rated power for effective peak shaving strategies. Moreover, a low initial SoC for the day is critical in achieving demand charge reduction.
Keywords:
battery energy storage system
demand charge reduction
distributed energy resources
linear optimization
optimal energy management
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

I
IEEE Milan PowerTech
IF:
0
Papers:
3
Citations:
0

Organization

U
university of north carolina
Scholars:
7.4W
Papers: 6.5W
Citations: 93
Cited Papers

Cited Papers

Citing Papers

Citing Papers