Energy Efficiency Using Genetic and Crow Search Algorithms in Smart Grid

被引:4
|
作者
Butt, Ayesha Anjum [1 ]
Rahim, Muhammad Hassan [1 ]
Khan, Mahnoor [1 ]
Zahra, Asma [1 ]
Tariq, Maham [1 ]
Ahmad, Tanveer [2 ]
Javaid, Nadeem [1 ]
机构
[1] COMSATS Inst Informat Technol, Islamabad 44000, Pakistan
[2] Goverment Coll Univ, Faisalabad 38000, Pakistan
关键词
D O I
10.1007/978-3-319-69835-9_6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Demand Side Management (DSM) is an efficient and robust strategy for energy management, Peak to Average Ratio (PAR) reduction and cost minimization. Many DSM techniques have been proposed for industrial, residential and commercial areas in last years. In this paper, we have design Home Energy Management Scheduler (HEMS) using two algorithms Genetic Algorithm (GA) and Crow Search Algorithm (CSA) for electricity cost and PAR minimization. Real Time Pricing (RTP) signals are used for electricity bill calculation. Simulation results demonstrate that our proposed scheme efficiently achieved our targeted objectives. However, GA performs superior than CSA due to high convergence rate. Furthermore, a trade-off exists between electricity cost and user waiting time; when electricity cost is low, user waiting time is high and vice versa.
引用
收藏
页码:63 / 75
页数:13
相关论文
共 50 条
  • [21] Generating customised experimental stimuli for visual search using Genetic Algorithms shows evidence for a continuum of search efficiency
    Verma, Milan
    McOwan, Peter W.
    VISION RESEARCH, 2009, 49 (03) : 374 - 382
  • [22] Enhancing Energy Efficiency in Mobile Ad hoc Networks using Genetic Algorithms
    Said, Khelifa
    Mekkakia, Maaza Zoulikha
    COMPUTACION Y SISTEMAS, 2020, 24 (03): : 1107 - 1119
  • [23] A comparative analysis of genetic algorithms and directed grid search for parametric optimization
    Srinivasan Sundhararajan
    Anil Pahwa
    Prakash Krishnaswami
    Engineering with Computers, 1998, 14 : 197 - 205
  • [24] Comparative analysis of genetic algorithms and directed grid search for parametric optimization
    Kansas State Univ, Manhattan, United States
    Eng Comput, 3 (197-205):
  • [25] A comparative analysis of Genetic Algorithms and Directed Grid Search for parametric optimization
    Sundhararajan, S
    Pahwa, A
    Krishnaswami, P
    ENGINEERING WITH COMPUTERS, 1998, 14 (03) : 197 - 205
  • [26] Impact of Smart Grid Intelligent Networks on Energy Efficiency Improvement
    Zawada, Marcin
    Pabian, Arnold
    Kuceba, Robert
    Bylok, Felicjan
    ICEME 2019: 019 10TH INTERNATIONAL CONFERENCE ON E-BUSINESS, MANAGEMENT AND ECONOMICS, 2019, : 221 - 225
  • [27] Smart Grid Considerations: Energy Efficiency vs. Security
    Berl, Andreas
    Niedermeier, Michael
    de Meer, Hermann
    ADVANCES IN COMPUTERS, VOL 88: GREEN AND SUSTAINABLE COMPUTING, PT 2, 2013, 88 : 159 - 198
  • [28] Algorithms for Smart Grid management
    Marah, Rim
    El Hibaoui, Abdelaaziz
    SUSTAINABLE CITIES AND SOCIETY, 2018, 38 : 627 - 635
  • [29] Using genetic algorithms to search for optimal projections
    Wallet, BC
    Marchette, DJ
    Solka, JL
    AUTOMATIC TARGET RECOGNITION VII, 1997, 3069 : 361 - 367
  • [30] In search of optimal clusters using genetic algorithms
    Murthy, CA
    Chowdhury, N
    PATTERN RECOGNITION LETTERS, 1996, 17 (08) : 825 - 832