面向多应用需求的分布式储能优化调度
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摘要
储能系统作为一种灵活的资源,在电力系统中发挥着重要作用,具备参与调峰、调压、提供备用等功能。针对该问题,提出了面向多应用需求的分布式储能优化调度模型。首先通过0-1变量的引入及对交流潮流的简化,解决了潮流双向流动的电力网络中难以考虑电压的问题。并基于此构建了以考虑煤耗成本、电压偏差惩罚的总运行成本最小为目标的分布式储能优化调度模型。该调度模型考虑了储能在电力调度中参与调峰、调压并提供备用容量等功能。为精确求解该模型,采用大M法将原有非线性模型转换成混合整数线性规划模型,并调用Gurobi求解器求解该模型。最后,基于修正的IEEE14节点系统,仿真验证了所提方法的有效性。
As a flexible resource, energy storage system plays an important role in the power system, possessing the functions of participating in peak shaving, voltage regulation, and providing backup, et al. Aiming at this problem, this paper proposes a distributed energy storage optimization scheduling model for multi-application requirements. Firstly, the introduction of binary variable and simplification of AC power flow solves the problem that it is difficult to consider the voltage in the power network with the bidirectional flow. Based on this, a distributed energy storage optimal scheduling model with minimum total operating cost considering coal consumption cost and voltage deviation penalty is constructed. The scheduling model considers the roles of energy storage in power dispatching to participate in peak shaving, voltage regulation and provide spare capacity. To solve the model accurately, the big M method is used to transform the original non-linear model into a mixed integer linear programming model, which is solved by calling Gurobi solver. Finally, based on the modified IEEE14 node system, simulation demonstrates the effectiveness of the proposed method.
As a flexible resource, energy storage system plays an important role in the power system, possessing the functions of participating in peak shaving, voltage regulation, and providing backup, et al. Aiming at this problem, this paper proposes a distributed energy storage optimization scheduling model for multi-application requirements. Firstly, the introduction of binary variable and simplification of AC power flow solves the problem that it is difficult to consider the voltage in the power network with the bidirectional flow. Based on this, a distributed energy storage optimal scheduling model with minimum total operating cost considering coal consumption cost and voltage deviation penalty is constructed. The scheduling model considers the roles of energy storage in power dispatching to participate in peak shaving, voltage regulation and provide spare capacity. To solve the model accurately, the big M method is used to transform the original non-linear model into a mixed integer linear programming model, which is solved by calling Gurobi solver. Finally, based on the modified IEEE14 node system, simulation demonstrates the effectiveness of the proposed method.
引文
[1]程时杰.大规模储能技术在电力系统中的应用前景分析[J].电力系统自动化,2013,37(1):3-8.Cheng Shijie.An analysis of prospects for application of large-scale energy storage technology in power systems[J].Automation of Electric Power Systems,2013,37(1):3-8(in Chinese).
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[13]李东东,徐连连,刘翔,等.考虑可削减负荷参与的含风光储微网经济优化调度[J].电力系统保护与控制,2017,45(2):35-41.Li Dongdong,Xu Lianlian,Liu Xiang,et al.Optimal dispatching of microgrid considering the participation of reducible loads,distributed generators and energy storage units[J].Power System Protection and Control,2017,45(2):35-41(in Chinese).
[14]张志昌,吴健,骆钊,等.计及储能运行特性的独立型交直流混合微网优化调度[J].电力系统自动化,2018,42(19):118-125.Zhang Zhichang,Wu Jian,Luo Zhao,et al.Optimal scheduling for independent AC/DC hybrid microgrid considering operation characteristics of energy storage[J].Automation of Electric Power Systems,2018,42(19):118-125(in Chinese).
[15]沈玉明,胡博,谢开贵,等.计及储能寿命损耗的孤立微电网最优经济运行[J].电网技术,2014,38(9):2371-2378.Shen Yuming,Hu Bo,Xie Kaigui,et al.Optimal economic operation of isolated microgrid considering battery life loss[J].Power System Technology,2014,38(9):2371-2378(in Chinese).
[16]甘伟,艾小猛,文劲宇,等.风-火-水-储-气联合优化调度策略[J].电工技术学报,2017,32(S1):11-20.Gan Wei,Ai Xiaomeng,Wen Jinyu,et al.Coordinated optimal operation of the wind,coal,hydro,gas units with energy storage[J].Transactions of China Electrotechnical Society,2017,32(S1):11-20(in Chinese).
[17]王扬,赵书强,徐岩,等.基于机会约束目标规划的风火储系统滚动调度[J].电网技术,2017,41(1):187-194.Wang Yang,Zhao Shuqiang,Xu Yan,et al.Rolling dispatch of wind/thermal/storage system based on chance constrained goal programming[J].Power System Technology,2017,41(1):187-194(in Chinese).
[18]李姚旺,苗世洪,尹斌鑫,等.考虑先进绝热压缩空气储能电站备用特性的电力系统优化调度策略[J].中国电机工程学报,2018,38(18):5392-5404.Li Yaowang,Miao Shihong,Yin Binxin,et al.Power system optimal scheduling strategy considering reserve characteristics of advanced adiabatic compressed air energy storage plant[J].Proceedings of the CSEE,2018,38(18):5392-5404(in Chinese).
[19]Jiang R W,Wang J H,Guan Y P.Robust unit commitment with wind power and pumped storage hydro[J].IEEE Transactions on Power Systems,2012,27(2):800-810.
[20]Conejo A,Cheng Y H,Zhang N,et al.Long-term coordination of transmission and storage to integrate wind power[J].CSEE Journal of Power and Energy Sytems,2017,3(1):36-43.
[21]Chen Y,Liu F,Mei S W,et al.An efficient MILP approximation for the hydro-thermal unit commitment[J].IEEE Transactions on Power Systems,2016,31(4):3318-3319.
[2]李相俊,王上行,惠东.电池储能系统运行控制与应用方法综述及展望[J].电网技术,2017,41(10):233-243.Li Xiangjun,Wang Shangxing,Hui Dong.Summary and prospect of operation control and application method for battery energy storage systems[J].Power System Technology,2017,41(10):233-243(in Chinese).
[3]中关村储能产业技术联盟.储能产业研究白皮书2018[R].北京:中关村储能产业技术联盟,2018.
[4]Li X J,Yao L Z,Hui D.Optimal control and management of a large-scale battery energy storage system to mitigate fluctuation and intermittence of renewable generations[J].Journal of Modern Power Systems&Clean Energy,2016,4(4):593-603.
[5]Li J,Ma Y,Mu G,et al.Optimal configuration of energy storage system coordinating wind turbine to participate power system primary frequency regulation[J].Energies,2018(11):1396.DOI:10.3390/en11061396.
[6]孙冰莹,刘宗歧,杨水丽,等.补偿度实时优化的储能-火电联合AGC策略[J].电网技术,2018,42(2):426-436.Sun Bingying,Liu Zongqi,Yang Shuili,et al.A real-time optimization method of compensation degree for storage coordinated with thermal power unit in AGC[J].Power System Technology,2018,42(2):426-436(in Chinese).
[7]Pand?i?H,Dvorkin Y,Carrión M.Investments in merchant energy storage:trading-off between energy and reserve markets[J].Applied Energy,2018(230):277-286.
[8]Han X,Liao S,Ai X,et al.Determining the minimal power capacity of energy storage to accommodate renewable generation[J].Energies,2017,10(4):468.
[9]廖庆龙,谢开贵,胡博.含风电和储能电力系统的时序随机生产模拟[J].电网技术,2017,41(9):2769-2776.Liao Qinglong,Xie Kaigui,Hu Bo.Sequential probabilistic production simulation of power systems with wind power and energy storage[J].Power System Technology,2017,41(9):2769-2776(in Chinese).
[10]李相俊,张晶琼,何宇婷,等.基于自适应动态规划的储能系统优化控制方法[J].电网技术,2016,40(5):1355-1362.Li Xiangjun,Zhang Jingqiong,He Yuting,et al.Optimal control method of energy storage system based on adaptive dynamic programming[J].Power System Technology,2016,40(5):1355-1362(in Chinese).
[11]赵书强,刘晨亮,王明雨,等.基于机会约束规划的储能日前优化调度[J].电网技术,2013,37(11):3055-3059.Zhao Shuqiang,Liu Chenliang,Wang Mingyu,et al.Chance constrained programming based day-ahead optimal scheduling of energy storage[J].Power System Technology,2013,37(11):3055-3059(in Chinese).
[12]杨德友,温佳鑫,蔡国伟,等.用于提高风电场可调度性的储能系统预测控制策略[J].高电压技术,2017,43(3):1043-1048.Yang Deyou,Wen Jiaxin,Cai Guowei,et al.Smoothing and dispatching the output of wind/battery energy storage hybrid system via model prediction control[J].High Voltage Engineering,2017,43(3):1043-1048(in Chinese).
[13]李东东,徐连连,刘翔,等.考虑可削减负荷参与的含风光储微网经济优化调度[J].电力系统保护与控制,2017,45(2):35-41.Li Dongdong,Xu Lianlian,Liu Xiang,et al.Optimal dispatching of microgrid considering the participation of reducible loads,distributed generators and energy storage units[J].Power System Protection and Control,2017,45(2):35-41(in Chinese).
[14]张志昌,吴健,骆钊,等.计及储能运行特性的独立型交直流混合微网优化调度[J].电力系统自动化,2018,42(19):118-125.Zhang Zhichang,Wu Jian,Luo Zhao,et al.Optimal scheduling for independent AC/DC hybrid microgrid considering operation characteristics of energy storage[J].Automation of Electric Power Systems,2018,42(19):118-125(in Chinese).
[15]沈玉明,胡博,谢开贵,等.计及储能寿命损耗的孤立微电网最优经济运行[J].电网技术,2014,38(9):2371-2378.Shen Yuming,Hu Bo,Xie Kaigui,et al.Optimal economic operation of isolated microgrid considering battery life loss[J].Power System Technology,2014,38(9):2371-2378(in Chinese).
[16]甘伟,艾小猛,文劲宇,等.风-火-水-储-气联合优化调度策略[J].电工技术学报,2017,32(S1):11-20.Gan Wei,Ai Xiaomeng,Wen Jinyu,et al.Coordinated optimal operation of the wind,coal,hydro,gas units with energy storage[J].Transactions of China Electrotechnical Society,2017,32(S1):11-20(in Chinese).
[17]王扬,赵书强,徐岩,等.基于机会约束目标规划的风火储系统滚动调度[J].电网技术,2017,41(1):187-194.Wang Yang,Zhao Shuqiang,Xu Yan,et al.Rolling dispatch of wind/thermal/storage system based on chance constrained goal programming[J].Power System Technology,2017,41(1):187-194(in Chinese).
[18]李姚旺,苗世洪,尹斌鑫,等.考虑先进绝热压缩空气储能电站备用特性的电力系统优化调度策略[J].中国电机工程学报,2018,38(18):5392-5404.Li Yaowang,Miao Shihong,Yin Binxin,et al.Power system optimal scheduling strategy considering reserve characteristics of advanced adiabatic compressed air energy storage plant[J].Proceedings of the CSEE,2018,38(18):5392-5404(in Chinese).
[19]Jiang R W,Wang J H,Guan Y P.Robust unit commitment with wind power and pumped storage hydro[J].IEEE Transactions on Power Systems,2012,27(2):800-810.
[20]Conejo A,Cheng Y H,Zhang N,et al.Long-term coordination of transmission and storage to integrate wind power[J].CSEE Journal of Power and Energy Sytems,2017,3(1):36-43.
[21]Chen Y,Liu F,Mei S W,et al.An efficient MILP approximation for the hydro-thermal unit commitment[J].IEEE Transactions on Power Systems,2016,31(4):3318-3319.