Improved Pareto Optimality Based on Multi-Objective Micro-Siting Planning of Offshore Wind Farm

doi:10.3969/j.issn.1000－7229.2017.04.014

Abstract

Abstract: To take the wind turbines wake effect, the economy and reliability of the collector system into account when starting to plan an offshore wind farm, the reliability of the collector system should be characterized by the number of wind

Turbine’s layers. With the wind turbine wake loss coefficient, the cost of submarine cables, and the number of wind turbine’s layers as the optimization targets, this paper establishes the multi-objective micro-siting planning model of the offshore wind farm, and obtains the optimal solution set through improved Pareto multi-objective optimization algorithm, finally makes the final optimization decision by analytic hierarchy process. Taking the distribution of wind resources in an offshore wind farm as an example, it verifies the mutual restraint relationship between the wind turbine wake loss, the connection submarine cables and the number of wind turbines layers, which should be taken into account in the planning progress. And the feasibility of the model and method is proved, evenly distributed alternative scheme can be obtained by improved Pareto optimization algorithm, analytic hierarchy process can choose the best plan based on the different requirements.

Key words: , offshore wind farm, micro-siting, Pareto optimality, collection system

CLC Number:

TM 614

TAN Maoqiang, HUANG Wei, CHE Wenxue, YAN Binyu, TAN Renshen. Improved Pareto Optimality Based on Multi-Objective Micro-Siting Planning of Offshore Wind Farm

[J]. Electric Power Construction, 2017, 38(4): 103-.

References

［1］徐乾耀, 康重庆, 张宁, 等. 海上风电出力特性及其消纳问题探讨［J］. 电力系统自动化, 2011, 35（22）: 54-59.

XU Qianyao, KANG Chongqing, ZHANG Ning, et al. A discussion on offshore wind power output characteristics and its accommodation［J］. Automation of Electric Power Systems, 2011, 35（22）: 54-59.

［2］王锡凡, 王碧阳, 王秀丽, 等. 面向低碳的海上风电系统优化规划研究［J］. 电力系统自动化, 2014, 38（17）: 4-13, 19.

WANG Xifan, WANG Biyang, WANG Xiuli, et al. Study of optimal planning methods for offshore wind power systems oriented low-carbon［J］. Automation of Electric Power Systems, 2014, 38（17）: 4-13, 19.

［3］刘林, 葛旭波, 张义斌, 等. 我国海上风电发展现状及分析［J］. 能源技术经济, 2012, 24（3）: 66-72.

LIU Lin, GE Xubo, ZHANG Yibin, et al. Analysis on status quo of China’s offshore wind power development［J］. Energy Technology and Economics, 2012, 24（3）: 66-72.

［4］WANG Z X, JIANG C W, AI Q, et al. The key technology of offshore wind farm and its new development in China［J］. Renewable and Sustainable Energy Reviews, 2009, 13（1）: 216-222.

［5］GONZALE J S, PAYAN M B, SANTOS J M R, et al. A review and recent developments in the optimal wind-turbine micro-siting problem［J］. Renewable and Sustainable Energy Reviews, 2014, 30: 133-144.

［6］GRADY S A, HUSSAINI M Y, ABDULLAH M M. Placement of wind turbines using genetic algorithms［J］. Renewable energy, 2005, 30（2）: 259-270.

［7］许昌, 杨建川, 李辰奇, 等. 复杂地形风电场微观选址优化［J］. 中国电机工程学报, 2013, 33（31）: 58-64.

XU Chang, YANG Jianchuan, LI Chenqi, et al. Optimization of wind farm layout in complex terrain ［J］. Proceedings of the CSEE, 2013, 33（31）: 58-64.

［8］严彦, 许昌, 刘德友, 等. 基于遗传算法的风电场微观选址优化研究［J］. 太阳能学报, 2013, 34（3）: 526-532.

YAN Yan, XU Chang, LIU Deyou, et al. Optimization research of wind farm micro sitting based on genetic algorithm［J］. Acta Energiae Solaris Sinica, 2013, 34（3）: 526-532.

［9］QUINONEZ-VARELA G, AULT G W, ANAYA-LARA O, et al. Electrical collector system options for large offshore wind farms［J］. IET Renewable Power Generation, 2007, 1（2）: 107-114.

［10］ACKERMANN T. Transmission system for offshore wind farms［J］. IEEE Power Engineering Review, 2002, 22（12）:23-27.

［11］符杨, 吴靖, 魏书荣. 大型海上风电场集电系统拓扑结构优化与规划［J］. 电网技术, 2013, 37（9）: 2553-2558.

FU Yang, WU Jing, WEI Shurong. Topology optimization and planning of power collection system for large-scale offshore wind farm［J］. Power System Technology, 2013, 37（9）: 2553-2558.

［12］黄玲玲, 符杨, 郭晓明. 海上风电场集电系统可靠性评估［J］. 电网技术, 2010, 34（7）: 169-174.

HUANG Lingling, FU Yang, GUO Xiaoming. Reliability evaluation of wind power collection system for offshore wind farm［J］. Power System Technology, 2010, 34（7）: 169-174.

［13］WU Y, LEE C, CHEN C, et al. Optimization of the wind turbine layout and transmission system planning for a large-scale offshore wind farm by AI technology［J］. IEEE Transactions on Industry Applications, 2014, 50（3）: 2071-2080.

［14］王一, 程浩忠. 计及输电阻塞的帕累托最优多目标电网规划［J］. 中国电机工程学报, 2008, 28（13）: 132-138.

WANG Yi, CHENG Haozhong. Pareto optimality based multi-objective transmission planning considering transmission congestion［J］. Proceedings of the CSEE, 2008, 28（13）: 132-138.

［15］盛四清, 范林涛, 李兴, 等. 基于帕累托最优的配电网多目标规划［J］. 电力系统自动化, 2014, 38（15）: 51-57.

SHENG Siqing, FAN Lintao, LI Xing, et al. Multi-objective planning of distribution network based on Pareto optimality［J］. Automation of Electric Power Sytems, 2014, 38（15）: 51-57.

[1]	LI Gang, MENG Yayun, DONG Wangying,WANG Tianjun. Multi-flow Modeling and Analysis on Cyber-Physical Energy System Based on Synergetic Theory [J]. Electric Power Construction, 2018, 39(5): 1-.
[2]	TIAN Shiming,BU Fanpeng, QI Linhai, LUO Yan. Frequent Pattern Mining and Knowledge Reasoning of Voltage Sag Events [J]. Electric Power Construction, 2018, 39(5): 21-.
[3]	HAN Naizheng, JIA Xiufang, XU Jianzhong, ZHAO Chengyong . Control Strategy for On-line Smooth Connection of Passive Modular Multilevel Converter Station via DC/DC Converter into DC Grid [J]. Electric Power Construction, 2018, 39(5): 28-.
[4]	JIANG Miao, XU Guangfu, LI Zhenghong, WEI Chengzhi, CHEN Jun. Analysis on Neutral Point Overvoltage during Grounded Fault in Distribution Network with Inverter-interfaced DGs and Countermeasures [J]. Electric Power Construction, 2018, 39(5): 70-.
[5]	WANG Dan，SUN Dongdong，HU Qinge，YUAN Kai， SUN Chongbo，SONG Yi，XU Jing，DING Chengdi . Demand Response of Electric Vehicles Based on Optimal Energy Status Regulation and Its Impact on Distribution Network [J]. Electric Power Construction, 2018, 39(5): 86-.
[6]	LI Bin，WU Qian，CHEN Songsong，LI Dezhi，YANG Bin，SUN Yi，QI Bing. Optimal Control Strategy for Domestic Electric Water Heaters Based on Cloud Model Theory [J]. Electric Power Construction, 2018, 39(5): 95-.
[7]	NING Yifei,CHEN Xingying, XIE Jun, YU Kun, LI Zuofeng, CHEN Zhenyu. Analysis on Response Characteristics of Public Buildings under Real-Time Price [J]. Electric Power Construction, 2018, 39(5): 105-.
[8]	CHEN Yixuan1，GUO Xiangyang2，LI Lingfang1，ZHU Xinchun1，XU Zheng2 . Frequency Deviation Peak Calculation of Sending-End Network in Large Asynchronous Interconnected Power Grid [J]. Electric Power Construction, 2018, 39(2): 30-.
[9]	ZHU Bingquan1, NI Qiulong1, XIANG Zhongming1, XU Lizhong1, CAO Yu2, GUO Chuangxin2 . Risk Tracing and Dynamic Control Technology for Whole Process of Power Grid Dispatching [J]. Electric Power Construction, 2018, 39(2): 36-.
[10]	ZHOU Yue, TAN Bendong, LI Miao, YANG Xuan, ZHOU Qiangming, ZHANG Zhenxing, TAN Min, YANG Jun . Transient Stability Assessment of Power System Based on Deep Learning Technology [J]. Electric Power Construction, 2018, 39(2): 103-.
[11]	LIN Qingming, HU Xu, BIAN Xiaoyan, LI Haixia, JIANG Ying. Multi-Turbine Equivalent Frequency Control Considering Wake Effect of Offshore Wind Farms [J]. Electric Power Construction, 2018, 39(2): 116-.
[12]	LI Bin, XIAO Hui, WEN Yafeng, LI Dezhi, CHEN Songsong, YANG Bin, CUI Gaoying. Cloud Service Mode Analysis of Smart Electricity Based on Block Chain [J]. Electric Power Construction, 2017, 38(9): 8-.
[13]	MA Qian, WANG Chen, LI Yang, WANG Zhe, ZHOU Lei. Investment Risk Analysis of Power Grid Enterprises Under Incremental Distribution Businesses Opening [J]. Electric Power Construction, 2017, 38(9): 139-.
[14]	LIANG Junjie, LAN Fei, NONG Zhigui, LI Jinghua . Probability Load Flow of Distribution Network with Considering Wind Power Nonlinear Correlation [J]. Electric Power Construction, 2017, 38(7): 34-.
[15]	LIU Dunnan, LI Qi, QIN Lijuan, ZHAO Jiawei. Evaluation of Grid Accepting Renewable Energy in Multi-Time Scale [J]. Electric Power Construction, 2017, 38(7): 44-.