Spatial electric load forecasting using an evolutionary heuristic

被引：3
|
作者：
Carreno E.M. [1 ]
Padilha-Feltrin A. [1 ]
Leal A.G. [2 ]
机构：
[1] Faculdade de Engenharia de Ilha Solteira, UNESP - Univ Estadual Paulista, Departamento de Engenharia Elétrica CP 31
[2] Elucid Solutions S/A, CEP 01228-904 São Paulo SP, Av. Angélica
来源：
Controle y Automacao | 2010年 / 21卷 / 04期
关键词：
Distribution planning; Knowledge extraction; Land use; Spatial electric load forecasting;
D O I：
10.1590/S0103-17592010000400005
中图分类号：
学科分类号：
摘要：
A method for spatial electric load forecasting using elements from evolutionary algorithms is presented. The method uses concepts from knowledge extraction algorithms and linguistic rules' representation to characterize the preferences for land use into a spatial database. The future land use preferences in undeveloped zones in the electrical utility service area are determined using an evolutionary heuristic, which considers a stochastic behavior by crossing over similar rules. The method considers development of new zones and also redevelopment of existing ones. The results are presented in future preference maps. The tests in a real system from a midsized city show a high rate of success when results are compared with information gathered from the utility planning department. The most important features of this method are the need for few data and the simplicity of the algorithm, allowing for future scalability.
引用
收藏
页码：379 / 388
页数：9
相关论文
共 50 条
  • [41] An advanced model for electric load forecasting
    Nastac, Dumitru Iulian
    Ulmeanu, Anatoli Paul
    2013 IEEE WORKSHOP ON INTEGRATION OF STOCHASTIC ENERGY IN POWER SYSTEMS (ISEPS), 2013, : 14 - 19
  • [42] A methodology for Electric Power Load Forecasting
    Almeshaiei, Eisa
    Soltan, Hassan
    ALEXANDRIA ENGINEERING JOURNAL, 2011, 50 (02) : 137 - 144
  • [43] Review of electric load forecasting methods
    Temraz, HK
    Salama, MMA
    Chikhani, AY
    1997 CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING, CONFERENCE PROCEEDINGS, VOLS I AND II: ENGINEERING INNOVATION: VOYAGE OF DISCOVERY, 1997, : 289 - 292
  • [44] Short - Term electric load forecasting using neural network models
    AlRashid, Y
    Paarmann, LD
    PROCEEDINGS OF THE 39TH MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS I-III, 1996, : 1436 - 1439
  • [45] Comprehensive Electric load forecasting using ensemble machine learning methods
    Bhatnagar, Mansi
    Dwivedi, Vivek
    Singh, Divyanshu
    Rozinaj, Gregor
    2022 29TH INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP), 2022,
  • [46] A improved SVM and its using in electric power system load forecasting
    Wang, Jingmin
    Ren, Guoqiao
    NEURAL INFORMATION PROCESSING, PT 1, PROCEEDINGS, 2006, 4232 : 847 - 855
  • [47] Electric Load Forecasting Model Using a Multicolumn Deep Neural Networks
    Hoori, Ammar O.
    Al Kazzaz, Ahmad
    Khimani, Rameez
    Motai, Yuichi
    Aved, Alex J.
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2020, 67 (08) : 6473 - 6482
  • [48] Short-term electric load forecasting using neural networks
    Ramezani, M
    Falaghi, H
    Haghifam, MR
    Shahryari, GA
    Eurocon 2005: The International Conference on Computer as a Tool, Vol 1 and 2 , Proceedings, 2005, : 1525 - 1528
  • [49] Electric Load Forecasting using Support Vector Machines for Robust Regression
    De Cosmis, Sonia
    De Leone, Renato
    Kropat, Erik
    Meyer-Nieberg, Silja
    Pickl, Stefan
    EMERGING M&S APPLICATIONS IN INDUSTRY AND ACADEMIA SYMPOSIUM AND THE MODELING AND HUMANITIES SYMPOSIUM 2013 (EAIA AND MATH 2013) - 2013 SPRING SIMULATION MULTI-CONFERENCE (SPRINGSIM'13), 2013, 45 (05): : 72 - 79
  • [50] Monthly Electric Load Forecasting Using Transfer Learning for Smart Cities
    Jung, Seung-Min
    Park, Sungwoo
    Jung, Seung-Won
    Hwang, Eenjun
    SUSTAINABILITY, 2020, 12 (16)
12345