PV Plus BESS表后应用的容量分析优化配置

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applied
sciences
Article
Optimal Configuration with Capacity Analysis of PV-Plus-BESS
for Behind-the-Meter Application
Cheng-Yu Peng
1
, Cheng-Chien Kuo
1,
* and Chih-Ta Tsai
2

 
Citation: Peng, C.-Y.; Kuo, C.-C.;
Tsai, C.-T. Optimal Configuration
with Capacity Analysis of
PV-Plus-BESS for Behind-the-Meter
Application. Appl. Sci. 2021, 11, 7851.
https://doi.org/10.3390/app11177851
Academic Editor: Pierluigi Siano
Received: 14 June 2021
Accepted: 22 August 2021
Published: 26 August 2021
Publishers Note: MDPI stays neutral
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Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1
Department of Electrical Engineering, National Taiwan University of Science and Technology,
Taipei 106335, Taiwan; d10107104@mail.ntust.edu.tw
2
Micro Grid and Energy Storage System Division, Smart Energy Business Unit, Tatung Company,
Taipei 10453, Taiwan; marco.tsai@tatung.com
* Correspondence: cckuo@mail.ntust.edu.tw
Abstract:
As the cost of photovoltaic (PV) systems and battery energy storage systems (BESS)
decreases, PV-plus-BESS applied to behind-the-meter (BTM) market has grown rapidly in recent
years. With user time of use rates (TOU) for charging and discharging schedule, it can effectively
reduce the electricity expense of users. This research uses the contract capacity of an actual industrial
user of 7.5 MW as a research case, and simulates a PV/BESS techno-economic scheme through the
HOMER Grid software. Under the condition that the electricity demand is met and the PV power
generation is fully used, the aim is to find the most economical PV/BESS capacity allocation and
optimal contract capacity scheme. According to the load demand and the electricity price, the analysis
shows that the PV system capacity is 8.25 MWp, the BESS capacity is 1.25 MW/3.195 MWh, and the
contract capacity can be reduced to 6 MW. The benefits for the economical solution are compared
as follows: 20-year project benefit, levelized cost of energy (LCOE), the net present cost (NPC), the
internal rate of return (IRR), the return on investment (ROI), discounted payback, total electricity
savings, renewable fraction (RF), and the excess electricity fraction. Finally, the sensitivity analysis of
the global horizontal irradiation, electricity price, key component cost, and real interest rate will be
carried out with the most economical solution by analyzing the impacts and evaluating the economic
evaluation indicators. The analysis method of this research can be applied to other utility users to
program the economic benefit evaluation of PV/BESS, especially an example for Taiwan’s electricity
prices at low levels in the world.
Keywords:
behind-the-meter; photovoltaic system; battery energy storage system; time of use
rates; electricity
1. Introduction
Over the past decade, renewable energy power experienced deployment growth and is
accompanied by decreases in system prices. This investment framework has evaluated the
effects of dominative public policies, time of use rates (TOU) pricing, low-cost technological
improvements, and identified circumstances to financial attraction to Photovoltaic (PV) plus
battery energy storage systems (BESS) in behind-the-meter (BTM) market [
1
]. To minimize
the price per kWh of levelized cost of energy (LCOE), the lithium-ion batteries are applied
to forecast the dynamics of cost metric in the context—a possible demonstration is its
usefulness as an optimally sized battery charged by a PV system [
2
]. The cost-effective
availability of BTM storage is economically viable to incentivize to increase the size in a
larger PV system of the optimally sized battery system. The low-cost PV and BESS systems
have the potential influence of fundamental shifts in the power sector structure in the
United States [
3
]. For a 3 kW/6 kWh BTM storage system in Australia, the reasonable and
practical assumptions would obtain around $80 per year on average, or up to $150 per year
in perfect operation over the most recent five years [4].
Appl. Sci. 2021, 11, 7851. https://doi.org/10.3390/app11177851 https://www.mdpi.com/journal/applsci
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