摘要
基于现阶段全球对清洁能源的需求越来越大,海上风电的装机容量逐年攀升,大规模海上风电系统成为未来发展方向,对海上汇集系统进行对比,分析海上直流风电场的前景和优势,对海上直流风电场拓扑结构进行归纳,建立基于现金折现估值模型的经济性分析模型,通过预测未来的现金流量进行估值,并采用改进粒子群算法分析得出最优及次优并网方案。采用最优及次优并网方案,对并网方式运用条件与场景提出供参考的选择方式。研究结果表明:经济性分析模型能有效将损耗和维护成本的年值折算为成本现值,实现典型并网方式的经济性评估。
In consideration of the fact that the global demand for clean energy, and the installed capacity of offshore wind power are both increased year by year, and large-scale offshore wind power system becomes a trend of the future development of wind power system, the prospect of the DC offshore wind farms and its advantages were analyzed, and the topology, advantages and disadvantages of the DC offshoe wind power farms were summarized, and an economy analysis model based on cash discount valuation model was established, which carried out the evaluation by predicting the future cash flow. An enhanced particle swarm optimization algorithm was adopted to obtain the optimal and suboptimal schemes for grid connection. The referred selection style for grid-connection pre-conditions and scenarios was put forward using the optimal and suboptimal schemes. The results show that the model can effectively convert the annual loss and maintenance cost into the present value of the cost, and realize a comparative analysis of the economic composition of the typical grid-connection modes.
作者
牛东晓
赵东来
杨尚东
雷霄
NIU Dongxiao;ZHAO Donglai;YANG Shangdong;LEI Xiao(School of Economics and Management,North China Electric Power University,Beijing 102206,China;Institute of Urban Energy Strategy and Planning,State Grid(Suzhou)Energy Research Institute,Suzhou 215000,China;China Electrical Power Research Institute,State Grid Simulation Center,Beijing 100192,China)
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2019年第12期3146-3155,共10页
Journal of Central South University:Science and Technology
基金
国家重点研发计划项目(2016YFB0901104)::国家自然科学基金资助项目(51307051)::中央高校基本科研业务费专项资金资助项目(2014ZP03,2015ZD01)~~
关键词
海上风电
汇集方式
并网方式
现金流折现估值模型
改进粒子群算法
offshore wind power
collection mode
grid connection mode
discounted cash flow model
enhanced particle swarm optimization algorithm
