CHP Economic Dispatch Considering Prohibited Zones to Sustainable Energy Using Self-Regulating Particle Swarm Optimization Algorithm

被引:0
|
作者
Afshin Lashkar Ara
Nastaran Mohammad Shahi
Mohammad Nasir
机构
[1] Islamic Azad University,Materials and Energy Research Center, Dezful Branch
来源
Iranian Journal of Science and Technology, Transactions of Electrical Engineering | 2020年 / 44卷
关键词
Combined heat and power (CHP); Optimization algorithm; Cogeneration units; Economic dispatch (ED); Self-regulating particle swarm optimization;
D O I
暂无
中图分类号
学科分类号
摘要
Economic dispatch is the optimal scheduling for generating units with technical constraints. Combined heat and power economic dispatch (CHPED) refers to minimization of the total energy cost for generating electricity and heat supply to load demand. This planning model integrates heat and power energy to balance energy supply and demand, mitigate climate change and improve energy efficiency of sustainable cities and green buildings. In this paper for the first time, self-regulating particle swarm optimization (SRPSO) algorithm is utilized for solving the CHPED problem by considering valve point effects and prohibited zones on fuel cost function of pure generation units and electrical power losses in transmission systems. The main advantage of SRPSO algorithm to PSO algorithm is the inertia weight flexibility with respect to search conditions. In this algorithm, unlike PSO algorithm that inertia weight reduces in each iteration, this value increases or reduces proportional to particles’ positions, which will lead particles to achieve optimal value with higher speed. The capability and effectiveness of the proposed algorithm are evaluated on a large-scale energy system using MATLAB environment. The results obtained by SRPSO algorithm are outperformed by other optimization methods from the economic, sustainable energy and time consumption point of view.
引用
收藏
页码:1147 / 1164
页数:17
相关论文
共 50 条
  • [1] CHP Economic Dispatch Considering Prohibited Zones to Sustainable Energy Using Self-Regulating Particle Swarm Optimization Algorithm
    Ara, Afshin Lashkar
    Shahi, Nastaran Mohammad
    Nasir, Mohammad
    IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING, 2020, 44 (03) : 1147 - 1164
  • [2] Improved particle swarm optimization for power economic dispatch with prohibited operating zones
    Chiang, C.-L. (t129@nkut.edu.tw), 1600, Advanced Institute of Convergence Information Technology, Myoungbo Bldg 3F,, Bumin-dong 1-ga, Seo-gu, Busan, 602-816, Korea, Republic of (04):
  • [3] Directionally Driven Self-Regulating Particle Swarm Optimization algorithm
    Tanweer, M. R.
    Auditya, R.
    Suresh, S.
    Sundararajan, N.
    Srikanth, N.
    SWARM AND EVOLUTIONARY COMPUTATION, 2016, 28 : 98 - 116
  • [4] Economic Dispatch Using Hybrid Particle Swarm Optimization with Prohibited Operating Zones and Ramp Rate Limit Constraints
    Prabakaran, S.
    Senthilkumar, V.
    Baskar, G.
    JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2015, 10 (04) : 1441 - 1452
  • [5] Improved bees algorithm for dynamic economic dispatch considering prohibited operating zones
    Sharma, Mahesh Kumar
    Phonrattanasak, Prakornchai
    Leeprechanon, Nopbhorn
    2015 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT ASIA), 2015,
  • [6] Dynamic Economic Dispatch Using Genetic and Particle Swarm Optimization Algorithm
    El Fergougui, A.
    Ladjici, A. A.
    Benseddik, A.
    Amrane, Y.
    2018 5TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT), 2018, : 1001 - 1005
  • [7] Economic Dispatch Considering Ancillary Service Based on Revised Particle Swarm Optimization Algorithm
    Ma, Xin
    Liu, Yong
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, 2010, 6215 : 175 - +
  • [8] Economic Dispatch incorporation Solar Energy using Particle Swarm Optimization
    Augusteen, W. A.
    Geetha, S.
    Rengaraj, R.
    2016 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL ENERGY SYSTEMS (ICEES), 2016, : 67 - 73
  • [9] Self regulating particle swarm optimization algorithm
    Tanweer, M. R.
    Suresh, S.
    Sundararajan, N.
    INFORMATION SCIENCES, 2015, 294 : 182 - 202
  • [10] Self-Regulating and Self-Perception Particle Swarm Optimization with Mutation Mechanism
    Yanjie Chen
    Jinglin Liang
    Yangning Wu
    Bingwei He
    Lixiong Lin
    Yaonan Wang
    Journal of Intelligent & Robotic Systems, 2022, 105