Pareto Optimal Prediction Intervals of Electricity Price

被引：51

作者：

Wan, Can ^{[1
]}

Niu, Ming ^{[2
]}

Song, Yonghua ^{[1
]}

Xu, Zhao ^{[2
]}

机构：

[1] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Peoples R China

[2] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2017年 / 32卷 / 01期

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Electricity price; extreme learning machine; NSGA-II; prediction intervals; EXTREME LEARNING-MACHINE; WIND POWER-GENERATION; NSGA-II; ALGORITHM;

D O I：

10.1109/TPWRS.2016.2550867

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This letter proposes a novel Pareto optimal prediction interval construction approach for electricity price combing extreme learning machine and non-dominated sorting genetic algorithm II (NSGA-II). The Pareto optimal prediction intervals are produced with respect to the formulated two objectives reliability and sharpness. The effectiveness of proposed approach has been verified through the numerical studies on Australia electricity market data.

引用

页码：817 / 819

页数：3

共 13 条

[1] Electricity Price Forecasting With Extreme Learning Machine and Bootstrapping [J].

Chen, Xia ;

Dong, Zhao Yang ;

Meng, Ke ;

Ku, Yan ;

Wong, Kit Po ;

Ngan, H. W. .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2012, 27 (04) :2055-2062

[2] A fast and elitist multiobjective genetic algorithm: NSGA-II [J].

Deb, K ;

Pratap, A ;

Agarwal, S ;

Meyarivan, T .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197

[3] Probabilistic forecasts, calibration and sharpness [J].

Gneiting, Tilmann ;

Balabdaoui, Fadoua ;

Raftery, Adrian E. .

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2007, 69 :243-268

[4] Application of NSGA-II Algorithm to Generation Expansion Planning [J].

Kannan, S. ;

Baskar, S. ;

McCalley, James D. ;

Murugan, P. .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2009, 24 (01) :454-461

[5] A fast and accurate online sequential learning algorithm for feedforward networks [J].

Liang, Nan-Ying ;

Huang, Guang-Bin ;

Saratchandran, P. ;

Sundararajan, N. .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2006, 17 (06) :1411-1423

[6] A Bi-Level Energy-Saving Dispatch in Smart Grid Considering Interaction Between Generation and Load [J].

Liu, Jichun ;

Li, Jie .

IEEE TRANSACTIONS ON SMART GRID, 2015, 6 (03) :1443-1452

[7] Electricity Price and Demand Forecasting in Smart Grids [J].

Motamedi, Amir ;

Zareipour, Hamidreza ;

Rosehart, William D. .

IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (02) :664-674

[8] Power utility nontechnical loss analysis with extreme learning machine method [J].

Nizar, A. H. ;

Dong, Z. Y. ;

Wang, Y. .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2008, 23 (03) :946-955

[9]

Robic T, 2005, LECT NOTES COMPUT SC, V3410, P520

[10] Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine [J].

Wan, Can ;

Xu, Zhao ;

Pinson, Pierre ;

Dong, Zhao Yang ;

Wong, Kit Po .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2014, 29 (03) :1033-1044

← 1 2 →