Demand Side Management Using Bacterial Foraging Optimization Algorithm

被引:9
作者
Esther, B. Priya [1 ]
Krishna, K. Shivarama [1 ]
Kumar, K. Sathish [1 ]
Ravi, K. [1 ]
机构
[1] VIT Univ, Sch Elect Engn, Vellore 632014, Tamil Nadu, India
来源
INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 1, INDIA 2016 | 2016年 / 433卷
关键词
Smart grid; Demand side management; Bacterial foraging optimization algorithm; Load shifting; DIRECT LOAD CONTROL;
D O I
10.1007/978-81-322-2755-7_68
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Demand side management (DSM) is one of the most significant functions involved in the smart grid that provides an opportunity to the customers to carryout suitable decisions related to energy consumption, which assists the energy suppliers to decrease the peak load demand and to change the load profile. The existing demand side management strategies not only uses specific techniques and algorithms but it is restricted to small range of controllable loads. The proposed demand side management strategy uses load shifting technique to handle the large number of loads. Bacterial foraging optimization algorithm (BFOA) is implemented to solve the minimization problem. Simulations were performed on smart grid which consists of different type of loads in residential, commercial and industrial areas respectively. The simulation results evaluates that proposed strategy attaining substantial savings as well as it reduces the peak load demand of the smart grid.
引用
收藏
页码:657 / 666
页数:10
相关论文
共 50 条
  • [31] Bacterial Foraging Optimization Algorithm for assembly line balancing
    Atasagun, Yakup
    Kara, Yakup
    NEURAL COMPUTING & APPLICATIONS, 2014, 25 (01) : 237 - 250
  • [32] Optimization learning of hidden Markov model using the bacterial foraging optimization algorithm for speech recognition
    Benmachiche, A.
    Makhlouf, A.
    Bouhadada, T.
    INTERNATIONAL JOURNAL OF KNOWLEDGE-BASED AND INTELLIGENT ENGINEERING SYSTEMS, 2020, 24 (03) : 171 - 181
  • [33] Bacterial Foraging Optimization Algorithm with Quorum sensing Mechanism
    Shen, Hai
    Zhang, Mo
    MECHATRONICS ENGINEERING, COMPUTING AND INFORMATION TECHNOLOGY, 2014, 556-562 : 3844 - 3848
  • [34] Genetic Algorithm Based Demand Side Management for Smart Grid
    C. Bharathi
    D. Rekha
    V. Vijayakumar
    Wireless Personal Communications, 2017, 93 : 481 - 502
  • [35] Multiobjective Genetic Algorithm for Demand Side Management of Smart Grid
    Hu, Xiao-Min
    Zhan, Zhi-Hui
    Lin, Ying
    Gong, Yue-Jiao
    Yu, Wei-Jie
    Hu, Yao-Xiu
    Zhang, Jun
    PROCEEDINGS OF THE 2013 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN SCHEDULING (CISCHED), 2013, : 14 - 21
  • [36] Bacterial Foraging Optimization Algorithm for assembly line balancing
    Yakup Atasagun
    Yakup Kara
    Neural Computing and Applications, 2014, 25 : 237 - 250
  • [37] Genetic Algorithm Based Demand Side Management for Smart Grid
    Bharathi, C.
    Rekha, D.
    Vijayakumar, V.
    WIRELESS PERSONAL COMMUNICATIONS, 2017, 93 (02) : 481 - 502
  • [38] Home Energy Management in Smart Grid Using Bacterial Foraging and Strawberry Algorithm
    Mushtaq, Noreen
    Rahim, Muhammad Hassan
    Khalid, Rabiya
    Abid, Samia
    Pamir
    Khan, Sajawal Ur Rehman
    Javaid, Nadeem
    ADVANCES ON BROAD-BAND WIRELESS COMPUTING, COMMUNICATION AND APPLICATIONS, BWCCA-2017, 2018, 12 : 547 - 559
  • [39] Demand Side Management in Smart Grid Using Load Shifting Technique
    Balakumar, P.
    Sathiya, S.
    2017 IEEE INTERNATIONAL CONFERENCE ON ELECTRICAL, INSTRUMENTATION AND COMMUNICATION ENGINEERING (ICEICE), 2017,
  • [40] Demand Side Management of Residential Loads in a Smart Grid using 2D Particle Swarm Optimization Technique
    Nayak, Sanjaya Kumar
    Sahoo, N. C.
    Panda, G.
    2015 IEEE POWER, COMMUNICATION AND INFORMATION TECHNOLOGY CONFERENCE (PCITC-2015), 2015, : 201 - 206