Load Forecasting in Electrical Distribution Grid of Medium Voltage

被引:11
|
作者
Chemetova, Svetlana [1 ]
Santos, Paulo [1 ]
Ventim-Neves, Mario [2 ]
机构
[1] Polytech Inst Setubal, Dept Elect Engn ESTSetubal, Rua Vale Chaves Estefanilha, P-2910761 Setubal, Portugal
[2] Univ Nova Lisboa, Dept Elect Engn, Fac Sci & Technol Quinta Torre, P-2829516 Caparica, Portugal
关键词
Electric power systems; Load forecasting; Smart-grids; Distribution systems; Electric substations; Artificial Neural Networks; NEURAL-NETWORK; DISTRIBUTION-SYSTEMS; ALGORITHM; ANN;
D O I
10.1007/978-3-319-31165-4_33
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The importance of forecasting has become more evident with the appearance of the open electricity market and the restructuring of the national energy sector. This paper presents a new approach to load forecasting in the medium voltage distribution network in Portugal. The forecast horizon is short term, from 24 h up to a week. The forecast method is based on the combined use of a regression model and artificial neural networks (ANN). The study was done with the time series of telemetry data of the DSO (EDP Distribution) and climatic records from IPMA (Portuguese Institute of Sea and Atmosphere), applied for the urban area of Evora - one of the first Smart Cities in Portugal. The performance of the proposed methodology is illustrated by graphical results and evaluated with statistical indicators. The error (MAPE) was lower than 5 %, meaning that chosen methodology clearly validate the feasibility of the test.
引用
收藏
页码:340 / 349
页数:10
相关论文
共 50 条
  • [41] Low Voltage Electrical Distribution Network Analysis under load variation
    Gruosso, G.
    Netto, R. S.
    Maffezzoni, P.
    Zhang, Z.
    Daniel, L.
    2018 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT), 2018, : 1248 - 1253
  • [42] Flower pollination–feedforward neural network for load flow forecasting in smart distribution grid
    Gaddafi Sani Shehu
    Nurettin Çetinkaya
    Neural Computing and Applications, 2019, 31 : 6001 - 6012
  • [43] Research on Grid Losses Reduction Measures for Medium and Low Voltage Distribution Network
    Zhang Yuze
    Wang Baihuai
    Wang Jingpeng
    An Rui
    Li Xiaodong
    He Yaqiao
    2020 5TH ASIA CONFERENCE ON POWER AND ELECTRICAL ENGINEERING (ACPEE 2020), 2020, : 668 - 672
  • [44] Construction of Analysis Models Applied in Secondary Grid of Medium Voltage Distribution Network
    Ge Shao-yun
    Liu Yang
    Liu Hong
    Han Jun
    2012 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2012,
  • [45] Grid Connection Studies for PV Power Plant in Medium Voltage Distribution Network
    Moshi, Godfrey Gladson
    Mgaya, Erick Vincent
    Mwakatage, Sithole Edwin
    2023 23rd International Scientific Conference on Electric Power Engineering, EPE 2023, 2023,
  • [46] Integration of Active Operation into the Planning Phase of a Medium-Voltage Distribution Grid
    Heise, Johannes
    Mostafa, Marwan
    Baboli, Payam Teimourzadeh
    Becker, Christian
    2024 INTERNATIONAL CONFERENCE ON RENEWABLE ENERGIES AND SMART TECHNOLOGIES, REST 2024, 2024,
  • [47] Real-Time Distribution Grid State Estimation with Limited Sensors and Load Forecasting
    Dobbe, Roel
    Arnold, Daniel
    Liu, Stephan
    Callaway, Duncan
    Tomlin, Claire
    2016 ACM/IEEE 7TH INTERNATIONAL CONFERENCE ON CYBER-PHYSICAL SYSTEMS (ICCPS), 2016,
  • [48] Technical and Economical Analysis of Medium Voltage Distribution Grid of Erzurum on Overload Condition
    Aksoy, Alkan
    Celebi, Mehmet
    Nuroglu, Fatih Mehmet
    2019 11TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ELECO 2019), 2019, : 69 - 75
  • [49] Smart Grid Voltage Control for Electrical Power Distribution System Operation Optimization
    Cespedes, Renato
    Reyes, Juan F.
    PROCEEDINGS OF THE 2016 IEEE ANDESCON, 2016,
  • [50] A Bottom-up Method for Probabilistic Short-Term Load Forecasting Based on Medium Voltage Load Patterns
    Jiang, Zhengbang
    Wu, Hao
    Zhu, Bingquan
    Gu, Wei
    Zhu, Yingwei
    Song, Yonghua
    Ju, Ping
    IEEE ACCESS, 2021, 9 : 76551 - 76563