A stochastic framework for the grid integration of wind power using flexible load approach

被引:44
作者
Heydarian-Forushani, E. [1 ]
Moghaddam, M. P. [2 ]
Sheikh-El-Eslami, M. K. [2 ]
Shafie-khah, M. [3 ]
Catalao, J. P. S. [3 ,4 ,5 ]
机构
[1] Iran Univ Sci & Technol, Tehran 1684613114, Iran
[2] Tarbiat Modares Univ, Tehran 14115111, Iran
[3] Univ Beira Interior, P-6201001 Covilha, Portugal
[4] INESC ID, P-1000029 Lisbon, Portugal
[5] Univ Lisbon, IST, P-1049001 Lisbon, Portugal
关键词
Wind power integration; Demand response programs; Flexible load; Stochastic programming; RENEWABLE ENERGY-SOURCES; DEMAND RESPONSE; UNIT COMMITMENT; HYBRID SYSTEM; PENETRATION; MANAGEMENT; RESOURCES; MARKET; OPERATION; DESIGN;
D O I
10.1016/j.enconman.2014.09.048
中图分类号
O414.1 [热力学];
学科分类号
摘要
Wind power integration has always been a key research area due to the green future power system target. However, the intermittent nature of wind power may impose some technical and economic challenges to Independent System Operators (ISOs) and increase the need for additional flexibility. Motivated by this need, this paper focuses on the potential of Demand Response Programs (DRPs) as an option to contribute to the flexible operation of power systems. On this basis, in order to consider the uncertain nature of wind power and the reality of electricity market, a Stochastic Network Constrained Unit Commitment associated with DR (SNCUCDR) is presented to schedule both generation units and responsive loads in power systems with high penetration of wind power. Afterwards, the effects of both price-based and incentive-based DRPs are evaluated, as well as DR participation levels and electricity tariffs on providing a flexible load profile and facilitating grid integration of wind power. For this reason, novel quantitative indices for evaluating flexibility are defined to assess the success of DRPs in terms of wind integration. Sensitivity studies indicate that DR types and customer participation levels are the main factors to modify the system load profile to support wind power integration. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:985 / 998
页数:14
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