Robust day-ahead coordinated scheduling of multi-energy systems with integrated heat-electricity demand response and high penetration of renewable energy

被引:35
|
作者
Lu, Jun [1 ]
Liu, Tianqi [1 ]
He, Chuan [1 ]
Nan, Lu [1 ]
Hu, Xiaotong [2 ]
机构
[1] Sichuan Univ, Coll Elect Engn, Chengdu 610065, Peoples R China
[2] State Grid Sichuan Elect Power Co, Dispatch & Control Ctr, Chengdu 610000, Peoples R China
关键词
Day-ahead scheduling; Power-to-Gas; Multi-energy system; Robust optimization; Integrated heat-electricity demand response; NATURAL-GAS; POWER; OPTIMIZATION; GENERATION; DISPATCH; STORAGE; LOADS; MODEL; UNIT;
D O I
10.1016/j.renene.2021.05.164
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As fossil fuels dry up and the proportion of renewable energy increases, multi-energy system (MES) becomes an effective way to realize renewable energy accommodation. High penetration of renewable energy brings challenges to the operation of power system, such as frequent curtailment of wind and the uncertainty of renewable energy threaten the security of the system. This paper proposes a two-stage robust scheduling model of MES considering integrated heat-electricity demand response (DR) to derive robust operation decisions. The proposed robust model minimizes the operation costs under base case scenario, while guaranteeing all operation constraints are met in any scenarios. Power-to-Gas (P2G) equipment which converts surplus wind and photovoltaic generation into natural gas is included to effectively reduce curtailment of renewable generation. Furthermore, integrated heat-electricity DR, fully utilizing the couplings among various systems, is proposed to decrease operation costs and enhance system security against uncertainties. Column-and-Constraint Generation (CCG) method is used to effectively solve the proposed robust model. Numerical results in MATLAB indicate that robust optimization ensures secure operation of the system, and the integrated heat-electricity DR could promote the accommodation of renewable energy as well as enhance economic benefits and robustness of the system. (c) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页码:466 / 482
页数:17
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