基于可再生能源配额制的风电并网节能经济调度
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摘要
中国将适时实施可再生能源配额制(简称配额制),这是中国电力体制改革的一项重要举措。配额制的实施将对电网公司的购电策略产生影响,从而改变火电和风电机组的调度计划。构建了配额制下的风电并网节能经济调度模型,对比分析了配额制实施前与实施后的火电和风电出力计划,从而研究了配额制的实施对风电消纳量的影响。根据文中实证结果,在节能经济调度的基础上,配额制的实施能够进一步促进风电消纳,风电出力提高了1.7%,弃风率下降了20%。此外,较高的配额比例(10%)和绿色证书交易价格(0.45元)有利于提高风电消纳量,降低弃风率。
In 2018 China plans to implement renewable portfolio standard(RPS), an important measure for the reform of China's electric power system. RPS implementation will impact on grid company's power purchase strategy, thereby changing the dispatch scheduling of thermal power and wind power. This paper establishes a energy-saving and economic dispatch model of power system containing wind power integration under RPS, and compares the output plans of thermal power and wind power before and after RPS implementation, thereby studying the impact of RPS on the amount of wind power's accommodation. Results show that RPS implementation can further promote accommodation of wind power on the basis of energy-saving and economic dispatch of power system, resulting in output increase 1.7% and curtailment decrease 20% of wind power. In addition, high RPS quota ratio(10%) and tradable green certificate transaction price(0.45 RMB Yuan) can further increase wind power accommodation and reduce its curtailment.
In 2018 China plans to implement renewable portfolio standard(RPS), an important measure for the reform of China's electric power system. RPS implementation will impact on grid company's power purchase strategy, thereby changing the dispatch scheduling of thermal power and wind power. This paper establishes a energy-saving and economic dispatch model of power system containing wind power integration under RPS, and compares the output plans of thermal power and wind power before and after RPS implementation, thereby studying the impact of RPS on the amount of wind power's accommodation. Results show that RPS implementation can further promote accommodation of wind power on the basis of energy-saving and economic dispatch of power system, resulting in output increase 1.7% and curtailment decrease 20% of wind power. In addition, high RPS quota ratio(10%) and tradable green certificate transaction price(0.45 RMB Yuan) can further increase wind power accommodation and reduce its curtailment.
引文
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[3]Zhang Y Z,Zhao X G,Ren L Z,et al.The development of China’s biomass power industry under feed-in tariff and renewable portfolio standard:A system dynamics analysis[J].Energy,2017(139):947-961.
[4]Zhao X G,Zhang Y Z,Ren L Z,et al.The policy effects of feed-in tariff and renewable portfolio standard:A case study of China’s waste incineration power industry[J].Waste Management,2017(68):711-723.
[5]Zhang Y,Zhao X,Zuo Y,et al.The development of the renewable energy power industry under feed-in tariff and renewable portfolio standard:a case study of china’s photovoltaic power industry[J].Sustainability,2017,9(4):532.
[6]赵新刚,刘晓蒙,兰贝.可再生能源配额制对优化我国电源结构的影响分析[J].可再生能源,2013,31(4):1-5.Zhao Xingang,Liu Xiaomeng,Lan Bei.Analysis of the influences of RPS on the optimization of power source structure in China[J].Renewable Energy Resources,2013,31(4):1-5(in Chinese).
[7]徐乾耀,康重庆,江长明,等.多时空尺度风电消纳体系初探[J].电力系统保护与控制,2013,41(1):28-32.Xu Qianyao,Kang Chongqing,Jiang Changming,et al.Preliminary analysis on wind power accommodation system from multiple temporal and spatial scale perspective[J].Power System Protection and Control,2013,41(1):28-32(in Chinese).
[8]司守奎,孙玺菁.LINGO软件及应用[M].北京:国防工业出版社,2017:1-2,180-187.
[9]王喆,余贻鑫,张弘鹏.社会演化算法在机组组合中的应用[J].中国电机工程学报,2004,24(4):12-17.Wang Zhe,Yu Yixin,Zhang Hongpeng.Social evolutionary programming based unit commitment[J].Proceedings of the CSEE,2004,24(4):12-17(in Chinese).
[10]盛四清,李亮亮,刘梦.考虑多重不确定因素的含风电场低碳经济调度[J].现代电力,2016,33(2):77-83.Sheng Siqing,Li Liangliang,Liu Meng.Low-carbon economic dispatch of power system integrated with wind farms by considering uncertainties factors[J].Modem Electric Power,2016,33(2):77-83(in Chinese).
[11]张娜娜.可再生能源配额制下的短期发电计划研究[D].上海:上海交通大学,2014.
[12]陆俊,彭文昊,朱炎平,等.基于粒子校正优化的智能小区需求响应调度策略[J].电网技术,2017,41(7):2370-2377.Lu Jun,Peng Wenhao,Zhu Yanping,et al.A scheduling strategy based on particle correction for intelligent power demand response[J].Power System Technology,2017,41(7):2370-2377(in Chinese).
[13]朱永胜,王杰,瞿博阳,等.采用基于分解的多目标进化算法的电力环境经济调度[J].电网技术,2014,38(6):1577-1584.Zhu Yongsheng,Wang Jie,Qu Boyang,et al.Environmental economic dispatch adopting multi-objective evolutionary algorithm based on decomposition[J].Power System Technology,2014,38(6):1577-1584(in Chinese).
[14]张海峰,高峰,吴江,等.含风电的电力系统动态经济调度模型[J].电网技术,2013,37(5):1298-1303.Zhang Haifeng,Gao Feng,Wu Jiang,et al.A dynamic economic dispatching model for power grid containing wind power generation system[J].Power System Technology,2013,37(5):1298-1303(in Chinese).