Intelligent management of battery system for energy arbitrage

被引:0
作者
de Souza, Jonas V. [1 ]
Momesso, Antonio E. C. [1 ]
Monteiro, Felipe M. dos S. [1 ]
Otto, Rodrigo B. [2 ]
Asada, Eduardo N. [1 ]
机构
[1] Univ Sao Paulo, Sao Carlos Sch Engn, Sao Carlos, Brazil
[2] Itaipu Technol Pk Fdn, Foz Do Iguao, Brazil
来源
2019 IEEE MILAN POWERTECH | 2019年
关键词
Energy Arbitrage; Energy Storage; Fuzzy System; Intelligent Management; STORAGE-SYSTEMS;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The demand for renewable energy sources has increased interest in storage systems, more specifically batteries. Due to their interesting characteristics, such as rapid response and decreasing price, the batteries can be used in various scenarios in the electrical system. Among them, one can highlight the profit from the purchase and sale of electricity. The objective of this work is to evaluate the battery operation employing a fuzzy system that helps on energy arbitrage. The fuzzy system is used as an automatic decision maker for buying or storing energy in the real-time operation of the system. The proposed fuzzy system is evaluated under two strategies varying the membership functions in order to achieve the highest profit. The results are promising, considering the profits obtained by the proposed fuzzy system well above of strategies based only on a comparison with median electricity market price.
引用
收藏
页数:6
相关论文
共 19 条
  • [1] NETWORK RECONFIGURATION IN DISTRIBUTION-SYSTEMS FOR LOSS REDUCTION AND LOAD BALANCING
    BARAN, ME
    WU, FF
    [J]. IEEE TRANSACTIONS ON POWER DELIVERY, 1989, 4 (02) : 1401 - 1407
  • [2] bel A. M., 2018, 2018 IEEE IND APPL S, P1
  • [3] Benincasa M, 2018, 2018 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR THE SEA
  • [4] LEARNING TO MEASURE SEA HEALTH PARAMETERS (METROSEA), P1, DOI 10.1109/MetroSea.2018.8657909
  • [5] Battery energy storage system for primary control reserve and energy arbitrage
    Brivio, Claudio
    Mandelli, Stefano
    Merlo, Marco
    [J]. SUSTAINABLE ENERGY GRIDS & NETWORKS, 2016, 6 : 152 - 165
  • [6] Multiobjective Intelligent Energy Management for a Microgrid
    Chaouachi, Aymen
    Kamel, Rashad M.
    Andoulsi, Ridha
    Nagasaka, Ken
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2013, 60 (04) : 1688 - 1699
  • [7] Heat recovery and storage installation in large-scale battery systems for effective integration of renewable energy sources into power systems
    Chen, Qun
    Zhao, Tian
    [J]. APPLIED THERMAL ENGINEERING, 2017, 122 : 194 - 203
  • [8] Energy Storage Modeling for Distribution Planning
    Dugan, R. C.
    Taylor, Jason A.
    Montenegro, Davis
    [J]. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2017, 53 (02) : 954 - 962
  • [9] FUZZY EXPERT SYSTEMS - AN APPLICATION TO SHORT-TERM LOAD FORECASTING
    HSU, YY
    HO, KL
    [J]. IEE PROCEEDINGS-C GENERATION TRANSMISSION AND DISTRIBUTION, 1992, 139 (06) : 471 - 477
  • [10] Karki RS, 2016, 2016 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS)