Energy network dispatch optimization under emergency of local energy shortage

被引:12
作者
Cai, Tianxing [1 ]
Zhao, Chuanyu [1 ]
Xu, Qiang [1 ]
机构
[1] Lamar Univ, Dan F Smith Dept Chem Engn, Beaumont, TX 77710 USA
关键词
Energy dispatch network; Emergency response plan; MILP; Optimization; MULTIPARAMETRIC PROGRAMMING APPROACH; ELECTRICITY; ALGORITHM;
D O I
10.1016/j.energy.2012.04.001
中图分类号
O414.1 [热力学];
学科分类号
摘要
The consequence of short-time energy shortage under extreme conditions, such as earthquake, tsunami, and hurricane, may cause local areas to suffer from delayed rescues, widespread power outages, tremendous economic losses, and even public safety threats. In such urgent events of local energy shortage, agile energy dispatching through an effective energy transportation network, targeting the minimum energy recovery time, should be a top priority. In this paper, a novel methodology is developed for energy network dispatch optimization under emergency of local energy shortage, which includes four stages of work. First, emergency-area-centered energy network needs to be characterized, where the capacity, quantity, and availability of various energy sources are determined. Second, the energy initial situation under emergency conditions needs to be identified. Then, the energy dispatch optimization is conducted based on a developed MILP (mixed-integer linear programming) model in the third stage. Finally, the sensitivity of the minimum dispatch time with respect to uncertainty parameters is characterized by partitioning the entire space of uncertainty parameters into multiple subspaces. The efficacy of the developed methodology is demonstrated via a case study with in-depth discussions. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:132 / 145
页数:14
相关论文
共 18 条
[1]   An efficient algorithm for convex multiparametric nonlinear programming problems [J].
Acevedo, J ;
Salgueiro, M .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2003, 42 (23) :5883-5890
[2]   A hybrid parametric/stochastic programming approach for mixed-integer linear problems under uncertainty [J].
Acevedo, J ;
Pistikopoulos, EN .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 1997, 36 (06) :2262-2270
[3]   An algorithm for multiparametric mixed-integer linear programming problems [J].
Acevedo, J ;
Pistikopoulos, EN .
OPERATIONS RESEARCH LETTERS, 1999, 24 (03) :139-148
[4]   A multiparametric programming approach for linear process engineering problems under uncertainty [J].
Acevedo, J ;
Pistikopoulos, EN .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 1997, 36 (03) :717-728
[5]   Energy management techniques to meet power shortage problems in India [J].
Bellarmine, GT ;
Arokiaswamy, NSS .
ENERGY CONVERSION AND MANAGEMENT, 1996, 37 (03) :319-328
[6]   Decision making in fuzzy environment and multicriteria power engineering problems [J].
Berredo, R. C. ;
Ekel, P. Ya. ;
Martini, J. S. C. ;
Palhares, R. M. ;
Parreiras, R. O. ;
Pereira, J. G., Jr. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2011, 33 (03) :623-632
[7]  
CPLEX, 2009, US CPLEX CALL LIB IN
[8]   A multiparametric programming approach for mixed-integer quadratic engineering problems [J].
Dua, V ;
Bozinis, NA ;
Pistikopoulos, EN .
COMPUTERS & CHEMICAL ENGINEERING, 2002, 26 (4-5) :715-733
[9]   MULTIPARAMETRIC LINEAR PROGRAMMING [J].
GAL, T ;
NEDOMA, J .
MANAGEMENT SCIENCE SERIES A-THEORY, 1972, 18 (07) :406-422
[10]  
GAMS, 2009, GAMS US GUID