提升风电场响应效能的混合储能最优经济配置
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摘要
在风力发电补贴越来越低,未来更可能取消补贴且电力市场辅助服务越来越完善的情况下,提出了一种以风电场AGC辅助服务性能与整体收益为目标的混合储能系统配置方法。首先,基于华北地区的两个细则,分析了AGC辅助服务的考核指标。然后,采用充放电次数限制少、充放电功率高的全钒液电池与成本低廉、容量较大的铅酸电池组成的混合储能系统,提出基于AGC服务性能指标和发电量有效上网率的响应效能指标,更好的反映加入储能系统的效果,并制定了储能系统充放电响应及SOC状态强制回归策略。基于计算效率高、全局收敛性能好的混沌蚁群算法,通过建立储能系统的成本子模型、风电场AGC服务收益及增加有效上网电量收益子模型,构建了以日收益最大为目标的优化配置模型。最后,通过计算某风电场储能系统的最优经济配置,分析了加入储能前后的响应效能与收益。结果表明:最优经济配置方法合理有效,加入储能系统后提升风电场约30%的综合性能收益。研究成果对未来风电场合理配置混合储能系统具有较大参考价值。
An AGC auxiliary service performance and overall benefit of wind farm-targeted allocation method for the hybrid energy storage system is proposed herein under the condition that the subsidies of wind power are getting lower and lower, and more likely to be abolished in the future, while the auxiliary services power market are more and more perfect. At first, the appraisal indicators for AGC auxiliary service are analyzed in accordance with two rules for the region of the North China. Afterwards, the AGC service performance index and the rate of power generation to effectively access grid-based response performance indexes are put forward, so as to better reflect the effect of adding energy storage system, and then the charge-discharge response and SOC state mandatory regression strategy of the energy storage system are made. A maximum daily benefit-targeted optimal allocation model is established through building up the cost model of the energy storage system, AGC service revenue and increasing the effective revenue. At last, the response performance and benefit before and after adding the energy storage are analyzed through the optimal economic allocation of the energy storage system for a wind farm. The result shows that the optimal economic allocation method is reasonable and effective; from which the comprehensive performance benefit of the wind farm is increased by about 30% after adding the energy storage system. The study result has a larger referential value for the reasonable allocation of wind farm energy storage system in the days to come.
An AGC auxiliary service performance and overall benefit of wind farm-targeted allocation method for the hybrid energy storage system is proposed herein under the condition that the subsidies of wind power are getting lower and lower, and more likely to be abolished in the future, while the auxiliary services power market are more and more perfect. At first, the appraisal indicators for AGC auxiliary service are analyzed in accordance with two rules for the region of the North China. Afterwards, the AGC service performance index and the rate of power generation to effectively access grid-based response performance indexes are put forward, so as to better reflect the effect of adding energy storage system, and then the charge-discharge response and SOC state mandatory regression strategy of the energy storage system are made. A maximum daily benefit-targeted optimal allocation model is established through building up the cost model of the energy storage system, AGC service revenue and increasing the effective revenue. At last, the response performance and benefit before and after adding the energy storage are analyzed through the optimal economic allocation of the energy storage system for a wind farm. The result shows that the optimal economic allocation method is reasonable and effective; from which the comprehensive performance benefit of the wind farm is increased by about 30% after adding the energy storage system. The study result has a larger referential value for the reasonable allocation of wind farm energy storage system in the days to come.
引文
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[3] 林艺城,孟安波,殷豪,等. 计及风电不确定性的区域互联动态经济优化调度方法[J]. 水利水电技术,2018,49(3):176- 185.
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[5] 马美婷,袁铁江,陈广宇,等.储能参与风电辅助服务综合经济效益分析[J].电网技术,2016,40(11):3362- 3367.
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[12] DELILLE G,FRANCOIS B,MALARANGE G.Dynamic frequency control support:a virtual inertia provided by distributed energy storage to isolated power systems[C]//ISGT. 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe) . Gothenburg:2010 IEEE PES,2010:1- 8.
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[14] 牛阳,张峰,张辉,等.提升火电机组AGC性能的混合储能优化控制与容量规划[J].电力系统自动化,2016,40(10):38- 45.
[15] 陈丽娟,姜宇轩,汪春.改善电厂调频性能的储能策略研究和容量配置[J].电力自动化设备,2017,37(8):52- 59.
[16] 丁冬,杨水丽,李建林.辅助火电机组参与电网调频的BESS容量配置[J].储能科学与技术,2014,3(4):302- 307.
[17] 丁明,徐宁舟,毕锐.用于平抑可再生能源功率波动的储能电站建模及评价[J].电力系统自动化,2011,35(2):66- 72.
[18] 赵俊,陈建军.基于混沌蚁群算法的大时滞对象神经网络控制[J].上海交通大学学报,2008,42(7):1198- 1202.
[19] 薛金花,叶季蕾,陶琼,等.采用全寿命周期成本模型的用户侧电池储能经济可行性研究[J].电网技术,2016,40(8):2471- 2476.
[2] 刘世林,文劲宇,孙海顺,等.风电并网中的储能技术研究进展[J].电力系统保护与控制,2013,41(23):145- 153.
[3] 林艺城,孟安波,殷豪,等. 计及风电不确定性的区域互联动态经济优化调度方法[J]. 水利水电技术,2018,49(3):176- 185.
[4] 李军徽,冯喜超,严干贵,等.高风电渗透率下的电力系统调频研究综述[J].电力系统保护与控制,2018,46(2):163- 170.
[5] 马美婷,袁铁江,陈广宇,等.储能参与风电辅助服务综合经济效益分析[J].电网技术,2016,40(11):3362- 3367.
[6] 国家发展改革委体改司.电力体制改革解读[M].北京:人民出版社,2015.
[7] 沈运帷,李扬,高赐威,等.需求响应在电力辅助服务市场中的应用[J].电力系统自动化,2017,41(22):151- 161.
[8] 乔颖,鲁宗相.考虑电网约束的风电场自动有功控制[J].电力系统自动化,2009,33(22):88- 93.
[9] 佘慎思,李征,蔡旭,等.用于平抑出力波动的风电场自动发电控制序列规划[J].中国电机工程学报,2015,35(10):2383- 2391.
[10] 柳伟,顾伟,孙蓉,等.DFIG-SMES 互补系统一次调频控制[J].电工技术学报,2012,27(9):108- 116.
[11] 胡泽春,罗浩成.大规模可再生能源接入背景下自动发电控制研究现状与展望[J].电力系统自动化,2018,42(8):2- 15.
[12] DELILLE G,FRANCOIS B,MALARANGE G.Dynamic frequency control support:a virtual inertia provided by distributed energy storage to isolated power systems[C]//ISGT. 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe) . Gothenburg:2010 IEEE PES,2010:1- 8.
[13] SERBAN I,TEODORESCU R,MARINESCU C.Analysis and optimization of the battery energy storage systems for frequency control in autonomous microgrids by means of hardware-in-the-loop simulations[C]//IEEE. 2012 3rd IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG).Aalborg:IEEE,2012:374- 379.
[14] 牛阳,张峰,张辉,等.提升火电机组AGC性能的混合储能优化控制与容量规划[J].电力系统自动化,2016,40(10):38- 45.
[15] 陈丽娟,姜宇轩,汪春.改善电厂调频性能的储能策略研究和容量配置[J].电力自动化设备,2017,37(8):52- 59.
[16] 丁冬,杨水丽,李建林.辅助火电机组参与电网调频的BESS容量配置[J].储能科学与技术,2014,3(4):302- 307.
[17] 丁明,徐宁舟,毕锐.用于平抑可再生能源功率波动的储能电站建模及评价[J].电力系统自动化,2011,35(2):66- 72.
[18] 赵俊,陈建军.基于混沌蚁群算法的大时滞对象神经网络控制[J].上海交通大学学报,2008,42(7):1198- 1202.
[19] 薛金花,叶季蕾,陶琼,等.采用全寿命周期成本模型的用户侧电池储能经济可行性研究[J].电网技术,2016,40(8):2471- 2476.
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