Economic dispatch of wind integrated power systems with energy storage considering composite operating costs

被引:28
作者
Chen, Houhe [1 ]
Zhang, Rufeng [1 ]
Li, Guoqing [1 ]
Bai, Linquan [2 ]
Li, Fangxing [2 ]
机构
[1] Northeast Dianli Univ, Dept Elect Engn, Jilin, Jilin, Peoples R China
[2] Univ Tennessee, Dept Elect Engn & Comp Sci, Knoxville, TN USA
基金
中国国家自然科学基金;
关键词
PARTICLE SWARM OPTIMIZATION; UNIT COMMITMENT; MODEL;
D O I
10.1049/iet-gtd.2015.0410
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
An economic dispatch (ED) model is proposed in this study for accommodating high penetrations of wind power with the integration of battery energy storage (BES) in power systems. In the proposed ED model, a wind-storage combined system (WSCS) model is studied to collectively mitigate the output fluctuations and improve the wind power utilisation. In addition, the proposed concept of composite operating costs include the unit operation cost, environmental cost, reserve cost, compensation cost for wind power curtailment, and energy loss cost of ES. With the minimisation of the composite operating costs as the objective function of the proposed ED model with WSCS, a modified bacterial foraging algorithm (MBFA) is proposed to solve the optimisation problem based on a combination of the bacterial foraging algorithm (BFA) and the Particle Swarm Optimisation (PSO). Furthermore, the case study on the IEEE 30-bus system has been used to demonstrate the feasibility and effectiveness of the proposed ED model and the performance improvement of the MBFA algorithm over BFA or PSO alone. The comparison between different scenarios shows that the integration of ES in the proposed model effectively improves the wind power utilisation and the system efficiency.
引用
收藏
页码:1294 / 1303
页数:10
相关论文
共 25 条
[1]   Adaptive Robust Optimization for the Security Constrained Unit Commitment Problem [J].
Bertsimas, Dimitris ;
Litvinov, Eugene ;
Sun, Xu Andy ;
Zhao, Jinye ;
Zheng, Tongxin .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2013, 28 (01) :52-63
[2]   Increasing the Flexibility of Combined Heat and Power for Wind Power Integration in China: Modeling and Implications [J].
Chen, Xinyu ;
Kang, Chongqing ;
O'Malley, Mark ;
Xia, Qing ;
Bai, Jianhua ;
Liu, Chun ;
Sun, Rongfu ;
Wang, Weizhou ;
Li, Hui .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2015, 30 (04) :1848-1857
[3]   Design and Control Strategies of an Induction-Machine-Based Flywheel Energy Storage System Associated to a Variable-Speed Wind Generator [J].
Cimuca, Gabriel ;
Breban, Stefan ;
Radulescu, Mircea M. ;
Saudemont, Christophe ;
Robyns, Benoit .
IEEE TRANSACTIONS ON ENERGY CONVERSION, 2010, 25 (02) :526-534
[4]   Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect [J].
Coelho, LS ;
Mariani, VC .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2006, 21 (02) :989-996
[5]   Planning and Operating Combined Wind-Storage System in Electricity Market [J].
Dicorato, Maria ;
Forte, Giuseppe ;
Pisani, Mariagiovanna ;
Trovato, Michele .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2012, 3 (02) :209-217
[6]   Economic power dispatch with cubic cost models using teaching learning algorithm [J].
Elanchezhian, E. B. ;
Subramanian, S. ;
Ganesan, S. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2014, 8 (07) :1187-1202
[7]   Dynamic adaptive bacterial foraging algorithm for optimum economic dispatch with valve-point effects and wind power [J].
Farhat, I. A. ;
El-Hawary, M. E. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2010, 4 (09) :989-999
[8]   Particle swarm optimization to solving the economic dispatch considering the generator constraints [J].
Gaing, ZL .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2003, 18 (03) :1187-1195
[9]   Multi-objective stochastic optimal planning method for stand-alone microgrid system [J].
Guo, Li ;
Liu, Wenjian ;
Jiao, Bingqi ;
Hong, Bowen ;
Wang, Chengshan .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2014, 8 (07) :1263-1273
[10]   An economic dispatch model incorporating wind power [J].
Hetzer, John ;
Yu, David C. ;
Bhattarai, Kalu .
IEEE TRANSACTIONS ON ENERGY CONVERSION, 2008, 23 (02) :603-611