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
  • [41] Control Strategy for PQ Improvement in an Autonomous Microgrid Using Bacterial Foraging Optimization Algorithm
    Chitra, N.
    Kumar, A. Senthil
    Priyadharshini, P.
    Shobana, K. M.
    ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY ALGORITHMS IN ENGINEERING SYSTEMS, VOL 2, 2015, 325 : 705 - 713
  • [42] Design of a Supplementary Controller for Power System Stabilizer Using Bacterial Foraging Optimization Algorithm
    Kiani, Mohammad
    Soloklo, Hasan Nasiri
    Mohammadi, M. Ali
    Farsangi, Malihe M.
    COMPUTATIONAL INTELLIGENCE AND INFORMATION TECHNOLOGY, 2011, 250 : 405 - 410
  • [43] AHHO: Arithmetic Harris Hawks Optimization algorithm for demand side management in smart grids
    Manzoor A.
    Judge M.A.
    Islam S.U.
    Neggaz N.
    Abulaigh L.
    Ahmad I.
    Discover Internet of Things, 2023, 3 (01):
  • [44] Array Synthesis Based on Mutational Bacterial Foraging Optimization Algorithm
    Meng, Yang
    Ren, Zuo-lin
    Tian, Yu-bo
    INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION ENGINEERING (CSIE 2015), 2015, : 220 - 226
  • [45] Efficient Demand Side Management Using a Novel Decentralized Building Automation Algorithm
    Spagkakas, Christodoulos
    Stimoniaris, Dimitrios
    Tsiamitros, Dimitrios
    ENERGIES, 2023, 16 (19)
  • [46] Impact of demand side management on the operational cost of microgrids using ABC algorithm
    Ullah, Kalim
    Quanyuan, Jiang
    Geng, Guangchao
    Khan, Rehan Ali
    Khan, Wahab
    FRONTIERS IN ENERGY RESEARCH, 2023, 10
  • [47] An Optimization Framework for Home Demand Side Management Incorporating Electric Vehicles
    Sherif, Hosam
    Zhu, Ziming
    Lambotharan, Sangarapillai
    2014 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT ASIA), 2014, : 57 - 61
  • [48] OPtimization of Home Energy Management System in Smart Grid for Effective Demand Side Management
    Anzar, Mahmood
    Iqra, Rafiq
    Kousar, Anila
    Ejaz, Shafaq
    Alvarez-Alvarado, Manuel S.
    Zafar, A. Khan
    PROCEEDINGS OF 2017 INTERNATIONAL RENEWABLE & SUSTAINABLE ENERGY CONFERENCE (IRSEC' 17), 2017, : 712 - 717
  • [49] Hourly load shifting approach for demand side management in smart grid using grasshopper optimisation algorithm
    Jamil, Majid
    Mittal, Sonam
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2020, 14 (05) : 808 - 815
  • [50] A Novel Load Management Algorithm for EMU by Implementing Demand Side Management Techniques using ANN
    Raju, M. Prathapa
    Laxmi, A. Jaya
    2017 INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTING TECHNOLOGIES AND APPLICATIONS (ICECTA), 2017, : 368 - 373