Heat production optimization using bio-inspired algorithms

被引:11
作者
Wozniak, Marcin [1 ]
Ksiazek, Kamil [1 ]
Marciniec, Jakub [2 ]
Polap, Dawid [1 ]
机构
[1] Silesian Tech Univ, Inst Math, Kaszubska 23, PL-44100 Gliwice, Poland
[2] Silesian Tech Univ, Fac Energy & Environm Engn, Konarskiego 18, PL-44100 Gliwice, Poland
关键词
Bio-inspired methods; Thermal systems optimization; Heat exchangers and pumps; Computational intelligence; DIFFERENTIAL EVOLUTION; SYSTEMS; SIMULATION; PARAMETERS; NETWORK; FOREST; ENERGY; FOSSIL; FUELS;
D O I
10.1016/j.engappai.2018.09.003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Energy efficiency of industrial systems is one of key features for optimal use of resources and the lowest costs of energy for users. In the recent time optimization of heating plants and heat distribution systems becomes an important venue for novel methods and innovative constructions. Various proposals can be seen for more efficient performance of heating systems in changing weather conditions. In this article results of using bio-inspired methods for intensification of the district heating plant to work with maximum efficiency at the lowest costs are presented. The research is focused on developing bio-inspired approaches for a mathematical model of a district heating plant in various weather conditions. The research model represents a sample district heating plant, in which circulation of hot water is performed in two heat exchangers supplied by controlled pumps. The system was calibrated with the use of proposed Polar Bear Optimization and the results were compared to one of best known heuristics, Particle Swarm Optimization. An objective function describing the operation. of the plant was developed and found applicable for proposed bio-inspired approach. The research results have shown that proposed methodology is efficient for all simulated weather conditions and various boundary conditions. Comparison the obtained results with non-optimal parameters confirms huge profits from applying right settings of the system.
引用
收藏
页码:185 / 201
页数:17
相关论文
共 50 条
  • [41] Synthesizing test scenarios in UMLactivity diagram using a bio-inspired approach
    Arora, Vinay
    Bhatia, Rajesh
    Singh, Maninder
    COMPUTER LANGUAGES SYSTEMS & STRUCTURES, 2017, 50 : 1 - 19
  • [42] Reprint of: Automated stem cell production by bio-inspired control
    Monostori, Laszlo
    Csaji, Balazs Cs
    Egri, Peter
    Kis, Krisztian B.
    Vancza, Jozsef
    Ochs, Jelena
    Jung, Sven
    Koenig, Niels
    Pieske, Simon
    Wein, Stephan
    Schmitt, Robert
    Brecher, Christian
    CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY, 2021, 34 : 84 - 94
  • [43] A Face Recognition Framework for Illumination Compensation Based on Bio-inspired Algorithms
    Plichoski, Guilherme Felippe
    Chidambaram, Chidambaram
    Parpinelli, Rafael Stubs
    2018 7TH BRAZILIAN CONFERENCE ON INTELLIGENT SYSTEMS (BRACIS), 2018, : 284 - 289
  • [44] True global optimality of the pressure vessel design problem: a benchmark for bio-inspired optimisation algorithms
    Yang, Xin-She
    Huyck, Christian
    Karamanoglu, Mehmet
    Khan, Nawaz
    INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 2013, 5 (06) : 329 - 335
  • [45] An Insight into Bio-inspired and Evolutionary Algorithms for Global Optimization: Review, Analysis, and Lessons Learnt over a Decade of Competitions
    Molina, Daniel
    LaTorre, Antonio
    Herrera, Francisco
    COGNITIVE COMPUTATION, 2018, 10 (04) : 517 - 544
  • [46] An efficient bio-inspired algorithm based on humpback whale migration for constrained engineering optimization
    Ghasemi, Mojtaba
    Deriche, Mohamed
    Trojovsky, Pavel
    Mansor, Zulkefli
    Zare, Mohsen
    Trojovska, Eva
    Abualigah, Laith
    Ezugwu, Absalom E.
    Mohammadi, Soleiman kadkhoda
    RESULTS IN ENGINEERING, 2025, 25
  • [47] Towards a bio-inspired design of a photovoltaic facade
    Assoa, Ya Brigitte
    Ratovonkery, Julie
    Menezo, Christophe
    Morlot, Rodolphe
    RENEWABLE ENERGY, 2024, 229
  • [48] Optimal probabilistic location of DGs using Monte Carlo simulation based different bio-inspired algorithms
    Hemeida, Mahmoud G.
    Alkhalaf, Salem
    Senjyu, Tomonobu
    Ibrahim, Abdalla
    Ahmed, Mahrous
    Bahaa-Eldin, Ayman M.
    AIN SHAMS ENGINEERING JOURNAL, 2021, 12 (03) : 2735 - 2762
  • [49] Hybrid bio-inspired scheduling algorithms for batch of tasks on heterogeneous computing system
    Sajid, Mohammad
    Raza, Zahid
    Shahid, Mohammad
    INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 2018, 11 (03) : 135 - 148
  • [50] Bio-inspired Network Optimization Based on Semi-Definite Programming
    Huang, Chao
    Zhang, Hao
    Wang, Zhuping
    Zhang, Changzhu
    2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 888 - 893