Sizing and Profitability of Energy Storage for Prosumers in Madeira, Portugal

被引:9
作者
Hashmi, Md Umar [1 ,2 ]
Cavaleiro, Jonathan [3 ]
Pereira, Lucas [4 ,5 ]
Btsic, Ana [1 ,2 ]
机构
[1] PSL Univ, INRIA, CNRS, Ecole Normale Super, Paris, France
[2] PSL Univ, CNRS, Ecole Normale Super, Comp Sci Dept, Paris, France
[3] M ITI Funchal, ITI, LARSyS, Madeira, Portugal
[4] Tecn Lisboa, LARSyS, ITI, Lisbon, Portugal
[5] Prsma Com, Funchal, Portugal
来源
2020 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT) | 2020年
基金
欧盟地平线“2020”;
关键词
OPTIMIZATION;
D O I
10.1109/isgt45199.2020.9087772
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a framework to select the best-suited battery for co-optimizing for peak demand shaving, energy arbitrage and increase self-sufficiency in the context of power network in Madeira, Portugal. Feed-in-tariff for electricity network in Madeira is zero, which implies consumers with excess production should locally consume the excess generation rather than wasting it. Further, the power network operator applies a peak power contract for consumers which imposes an upper bound on the peak power seen by the power grid interfaced by energy meter. We investigate the value of storage in Madeira, using four different types of prosumers, categorized based on the relationship between their inelastic load and renewable generation. We observe that the marginal increase in the value of storage deteriorates with increase in size and ramping capabilities. We propose the use of profit per cycle per unit of battery capacity and expected payback period as indices for selecting the best-suited storage parameters to ensure profitability. This mechanism takes into account the consumption and generation patterns, profit, storage degradation, and cycle and calendar life of the battery. We also propose the inclusion of a friction coefficient in the original co-optimization formulation to increase the value of storage by reducing the operational cycles and eliminate low returning transactions.
引用
收藏
页数:5
相关论文
共 27 条
[1]  
ACIF-CCIM LIBAL and DTU, 2018, 46 EUR COMM
[2]   Co-optimizing the value of storage in energy and regulation service markets [J].
Anderson K. ;
El Gamal A. .
Energy Systems, 2017, 8 (02) :369-387
[3]  
[Anonymous], 2019, SMA SUNNY BOY 2 0 CO
[4]  
[Anonymous], 2019, A behind the scenes take on lithium-ion battery prices | bloombergnef," julho
[5]  
Aquino C. Z. Todd, 2017, 10060535OZPC1001 HDR
[6]   Reliability-Constrained Optimal Sizing of Energy Storage System in a Microgrid [J].
Bahramirad, Shaghayegh ;
Reder, Wanda ;
Khodaei, Amin .
IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (04) :2056-2062
[7]   Optimal Energy Storage Sizing and Control for Wind Power Applications [J].
Brekken, Ted K. A. ;
Yokochi, Alex ;
von Jouanne, Annette ;
Yen, Zuan Z. ;
Hapke, Hannes Max ;
Halamay, Douglas A. .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2011, 2 (01) :69-77
[8]   Sizing of Energy Storage for Microgrids [J].
Chen, S. X. ;
Gooi, H. B. ;
Wang, M. Q. .
IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (01) :142-151
[9]  
Chen Y., 2019, INNOV SMART GRID TEC, P1
[10]   Co-Optimizing Battery Storage for the Frequency Regulation and Energy Arbitrage Using Multi-Scale Dynamic Programming [J].
Cheng, Bolong ;
Powell, Warren B. .
IEEE TRANSACTIONS ON SMART GRID, 2018, 9 (03) :1997-2005