含新能源微电网负荷响应的二阶电力模型研究
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摘要
随着全球性的能源紧张,新能源已成为替代传统化石能源的重要手段,当新能源的随机性给电网调度带来新的挑战。以新能源接入微电网为例,建立一种两阶段的电力市场模型,并提出一种需求侧响应定价策略。模型第一阶段针对新能源预测出力,在预测需求侧响应基础上,确定微电网出清电价。第二阶段在新能源随机处理,各用户提出的需求侧响应基础上,确定微电网调整电价。算例分析的结果表明,所提模型能够利用用户不同的需求侧响应曲线,调整系统的负荷水平,从而有利于新能源接入。
With the global energy shortage,renewable energy has become an important means to replace traditional fossil energy. When the randomness of renewable energy brings new challenges to power grid dispatching,taking the new energy access microgrid as an example,this paper establishes a two-stage power market model and proposes a demand side response pricing strategy. In the first stage of the model,the new energy forecast is made. Based on the predicted demand side response,the micro-grid clears the electricity price. In the second stage,based on the random processing of new energy and the demand side response proposed by each user,the micro-grid is adjusted to adjust the electricity price. The results of the example analysis show that the proposed model can use different demand side response curves of users to adjust the load level of the system,thus facilitating new energy access.
With the global energy shortage,renewable energy has become an important means to replace traditional fossil energy. When the randomness of renewable energy brings new challenges to power grid dispatching,taking the new energy access microgrid as an example,this paper establishes a two-stage power market model and proposes a demand side response pricing strategy. In the first stage of the model,the new energy forecast is made. Based on the predicted demand side response,the micro-grid clears the electricity price. In the second stage,based on the random processing of new energy and the demand side response proposed by each user,the micro-grid is adjusted to adjust the electricity price. The results of the example analysis show that the proposed model can use different demand side response curves of users to adjust the load level of the system,thus facilitating new energy access.
引文
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[3]吴雄,王秀丽,王建学,等.微网经济调度问题的混合整数规划方法[J].中国电机工程学报,2013,33(28):2-8.Wu Xiong,Wang Xiuli,Wang Jianxue,et al. Economic Generation Scheduling of a Microgrid using Mixed integer programming[J]. Proceedings of the CSEE,2014,34(29):5063-5072.
[4] Marnay C,Venkataramanan G,Stadler M,et al. Optimal technology selection and operation of commercial building microgrid[J]. Power Systems,IEEE Transactions on,2008,23(3):975-982.
[5]顾伟,吴志,王锐.考虑污染气体排放的热电联供型微电网多目标运行优化[J].电力系统自动化,2012,36(14):177-185.Gu Wei,Wu Zhi,Wang Rui,et al. Multi-objective Optimization of Combined Heat and Power Microgrid Considering Pollutant Emission[J]. Automation of Electric Power Systems,2012,36(14):177-185.
[6] Campanari S,Macchi E. Technical and tariff scenarios effect on microturbine trigenerative applications[J]. Journal of Engineering for Gas Turbines and Power,2004,126(3):581-589.
[7] Swider D J. Compressed air energy storage in an electricity system with significant wind power generation[J]. Energy Conversion,IEEE Transactions on,2007,22(1):95-102.
[8]郑乐,胡伟,陆秋瑜,等.储能系统用于提高风电接入的规划和运行综合优化模型[J].中国电机工程学报,2014,34(16):2533-2543.Zheng Le,Hu Wei,Lu Qiuyu,et al. Research on Planning and Operation Model for Energy Storage System to Optimize Wind Power Integration[J]. Proceedings of the CSEE,2014,34(16):2533-2543.
[9]徐飞,闵勇,陈磊,等.包含大容量储热的电-热联合系统[J].中国电机工程学报,2014,34(29):5063-5072.Xu Fe,Min Yong,Chen Lei,et al. Combined Electricity-Heat Operation System Containing Large Capacity Thermal Energy Storage[J]. Proceedings of the CSEE,2014,34(29):5063-5072.
[10]Pandian M S,Anwari M,Husodo B Y,et al. Efficiency and economics analysis of Proton Exchange Membrane fuel cell[C]//IPEC,2010 Conference Proceedings. IEEE,2010:875-880.
[11]Tsikalakis A G,Hatziargyrion N D. Centralized control for optimizing microgrid operation[J]. IEEE Transactions on Energy Conversion,2008,23(1):241-248.
[12]郭力,许东,王成山,等.冷电联供分布式供能系统能量优化管理[J].电力系统自动化,2009,(19):96-100.Guo Li,Xu Dong,Wang Chengshan,et al. Energy Optimization and Management of Combined Cooling and Power Distributed Energy Supply System[J]. Automation of Electric Power Systems,2009,(19):96-100.
[13]向月,刘俊勇,魏震波,等.考虑可再生能源出力不确定性的微电网能量优化鲁棒模型[J].中国电机工程学报,2014,34(19):3063-3072.Xiang Yue,Liu Junyong,Wei Zhenbo,et al. Robust Model of Microgrid Energy Optimization With Uncertain Renewable Energy Sources[J]. Proceedings of the CSEE,2014,34(19):3063-3072.