Distributed Generation Planning for Distribution Network Based on Modified Bat Algorithm

FAN Bin, ZHOU Lixing, HUANG Di, LIU Jiajun, LIU Bowei, ZHU Lingfeng

Electric Power Construction ›› 2015, Vol. 36 ›› Issue (3) : 123-128.

PDF(559 KB)
PDF(559 KB)
Electric Power Construction ›› 2015, Vol. 36 ›› Issue (3) : 123-128. DOI: 10.3969/j.issn.1000-7229.2015.03.022

Distributed Generation Planning for Distribution Network Based on Modified Bat Algorithm

  • FAN Bin, ZHOU Lixing, HUANG Di, LIU Jiajun, LIU Bowei, ZHU Lingfeng
Author information +
History +

Abstract

Rational planning of distributed generation in power grid can improve the energy efficiency and the economy, reliability and flexibility operation of power system. This paper constructed the multi-objective planning model with minimizing total investment cost in the construction and operation of the distributed power system and the power loss of system, as well as maximizing the investment the static voltage stability index as optimization subgoals. This paper used and improved a new bionic algorithm-bat algorithm, which could effectively solve the problems of easily trapping into local optimal solution and slow convergence speed in the later stage. Then, 14-node distribution network test systems were used to simulate and analyze the location and capacity of distributed generation. The simulation results show that, compared with the traditional bat algorithm and particle swarm optimization, the improved bat algorithm can better and faster get the optimal planning scheme of distributed generation connected to distribution network, which can validate the correctness and feasibility of the algorithm.

Key words

distributed generation / bat algorithm / multi-objective optimization / distribution network / optimal location

Cite this article

Download Citations
FAN Bin, ZHOU Lixing, HUANG Di, LIU Jiajun, LIU Bowei, ZHU Lingfeng. Distributed Generation Planning for Distribution Network Based on Modified Bat Algorithm[J]. Electric Power Construction. 2015, 36(3): 123-128 https://doi.org/10.3969/j.issn.1000-7229.2015.03.022

References

[1]庄园,王磊.分布式电源在配电网络中优化选址与定容的研究[J]. 电力系统保护与控
制,2012,40(20):73-78.
Zhuang Yuan,Wang Lei. Research of distributed generation optimal layout and capacity confirmation in distribution network[J
]. Power System Protection and Control, 2012,40(20):73-78.
[2]Mendez Q V H,Rivier A J,Gomez S R T. Assessment of energy distribution losses for increasing penetration of
distributed generation[J].IEEE Transactions on Power Systems,2006,21(2):533-540.
余娟,孙鸣,邓博.DG的孤岛运行方式及其对保护与控制的影响[J].电力建设,2009,30(6):21-24.
[3]Yu Juan, Sun Ming, Deng Bo. DG islet operation mode and its impact on protection and control[J].Electric Power
Construction,2009,30(6):21-24.
[4]汪宁渤,马彦宏,王建东.大规模风电集中并网对电力系统安全稳定的影响[J].电力建设,2011,32(11):77-80.
Wang Ningbo, Ma Yanhong, Wang Jiandong. Analysis of power system security and stability caused by large-scale wind power grid
integration[J].Electric Power Construction,2011,32(11):77-80.
[5]邱晓燕,夏莉丽,李兴源.智能电网建设中分布式电源的规划[J].电网技术,2010,34(4):7-10.
Qiu Xiaoyan, Xia Lili, Li Xingyuan. Planning of distributed generation in construction of smart grid[J].Power System
Technology, 2010,34(4):7-10.
[6]张节潭,程浩忠,姚良忠,等. 分布式风电源选址定容规划研究[J]. 中国电机工程学报, 2009, 29(16): 1-7.
Zhang Jietan, Cheng Haozhong, Yao Liangzhong, et al. Study on siting and sizing of distributed wind generation[J].
Proceedings of the CSEE, 2009,29(16):1-7.
[7]叶德意,何正友, 臧天磊. 基于自适应变异粒子群算法的分布式电源选址与容量确定[J]. 电网技术, 2011, 35(6): 154-159.
Ye Deyi,He Zhengyou,Zang Tianlei. Siting and sizing of distributed generation planning based on adaptive mutation particle
swarm optimization algorithm[J]. Power System Technology, 2011, 35(6): 154-159.
[8]丁明,石雪梅. 基于遗传算法的电力市场环境下电源规划的研究[J]. 中国电机工程学报, 2006, 26(21): 43-49.
Ding Ming,Shi Xuemei. Study of Generation expansion planning based on genetic algorithms in the environment of electricity
market[J]. Proceeding of the CSEE, 2006, 26(21): 43-49.
[9]Yang X S .A new metaheuristic bat-inspired algorithm [M]// Nature Inspired Cooperative Strategies for Optimization.
Berlin: Springer-Verlag,2010:65-74.
[10]Bora T C,Coelho L D S,Lebensztajn L. Bat-inspired optimization approach for the brushless DC wheel motor problem[J]
. IEEE Transactions on Magnetics,2012, 48(2):947-950.
[11]黄光球,赵魏娟,陆秋琴.求解大规模优化问题的可全局收敛蝙蝠算法[J].计算机应用研究,2013,30(5):1323-1328.
Huang Guangqiu,Zhao Weijuan,Lu Qiuqin. Bat algorithm with global convergence for solving large-scale optimization problem[
J].
Application Research of Computers, 2013,30(5):1323-1328.
[12]Hamid F,Mahmood-Reza H.ACO based algorithm for distributed generation sources allocation and sizing in distribution
systems[C]//2007 IEEE Power Tech.Lausanne:2007:555-560.
[13]盛晓华,叶春明.蝙蝠算法在PFSP调度问题中的应用研究[J].工业工程,2013,16(1):119-124.
Sheng Xiaohua,Ye Chunming .Application of bat algorithm to permutation flow-shop scheduling problem[J]. Industrial
Engineering Journal, 2013,16(1):119-124.
[14]李枝勇,马良,张惠珍.0-1规划问题的元胞蝙蝠算法[J].计算机应用研究,2013,30(10):2093-2906.
Li Zhiyong,Ma Liang,Zhang Huizhen. Cellular bat algorithm for 0-1 programming problem[J]. Application Research of
Computers, 2013,30(10):2093-2906.
[15]刘长平,叶春明.具有混沌搜索策略的蝙蝠优化算法及性能仿真[J].系统仿真学报,2013,25(6):1183-1188.
Liu Changping, Ye Chunming. Bat algorithm with chaotic search strategy and analysis of its property[J]. Journal of System
Simulation, 2013,25(6):1183-1188.
[16]刘长平,叶春明,刘满城.来自大自然的寻优策略:像蝙蝠一样感知[J].计算机应用研究,2013,30(5):1320-1322.
Liu Changping,Ye Chunming,Liu Mancheng. Optimization strategy from nature: Perceive as bat[J]. Application Research of
Computers, 2013,30(5):1320-1322.
PDF(559 KB)

Accesses

Citation

Detail

Sections
Recommended

/