Hydraulic-Thermal Cooperative Optimization of Integrated Energy Systems: A Convex Optimization Approach

被引:38
|
作者
Lu, Shuai [1 ]
Gu, Wei [1 ]
Zhang, Cuo [2 ]
Meng, Ke [2 ]
Dong, Zhaoyang [2 ]
机构
[1] Southeast Univ, Sch Elect Engn, Nanjing 210096, Peoples R China
[2] Univ New South Wales, Sch Elect Engn & Telecommun, Sydney, NSW 2052, Australia
基金
美国国家科学基金会;
关键词
Pipelines; Hydraulic systems; Boilers; Optimization; Indexes; Batteries; Convex optimization; district heating network; feasible solution recovery; hydraulic and thermal conditions; integrated energy systems; second-order conic relaxation; DISTRICT-HEATING NETWORK; OPTIMAL POWER-FLOW; OPTIMAL OPERATION; ELECTRICITY; DISPATCH; RELAXATION; MICROGRIDS; PROGRAMS; STORAGE; DRIVEN;
D O I
10.1109/TSG.2020.3003399
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
The integrated energy systems (IESs) that combine multiple heterogeneous energy systems such as power, natural gas, and district heating systems, are believed to have high potentials in future energy systems owing to their advantages in economy, energy efficiency, and promoting renewable energy consumption. The complicated hydraulic and thermal operating conditions of the district heating network (DHN) render the dispatch of IESs a nonlinear and nonconvex optimization problem that is computationally intractable. To address this problem, firstly, we propose a hydraulic-thermal cooperative optimization (HTCO) model for the operation of IESs. Secondly, the DHN model is reformulated by introducing auxiliary variables to reduce the complexity, based on which the HTCO model is converted into a nonconvex quadratically constrained programming (NCQCP). Thirdly, a second-order conic relaxation model is proposed for the NCQCP model, and a penalty model is introduced based on the convex-concave procedure to reduce the relaxation errors. Finally, an iterative algorithm with efficient stopping criteria is developed for the HTCO model to find a local optimum, in which low optimality gaps (similar to 5.3% for the small case and similar to 2.4% for the big case) are numerically observed. Case studies verify the effectiveness of the proposed methods.
引用
收藏
页码:4818 / 4832
页数:15
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