电–气互联系统的气电解耦分布式多目标优化调度
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摘要
本文基于能源互联网背景建立了一种计及供能成本、碳排放量和净负荷曲线平滑度的电–气互联系统多目标优化模型,并采用线性化方法将非线性优化模型转化为混合整数线性规划模型.同时,为了求解该模型,实现各能源的协同互补利用,提高能源的利用率,本文在保障各能源网络分散自治权的基础上提出一种基于气电解耦的分布式多目标优化算法,以气电解耦优化的方式实现电、气系统的分散自治.所提算法将原系统的多目标优化问题分解为电网和气网的子优化问题,并采用独立的优化器完成子问题的求解.电网和气网仅需交换少量边界变量以及虚拟目标因子分别进行全局调整即可获得多目标解.最后,本文根据修改的IEEE 39节点电力网络和比利时20节点天然气网络搭建模型并进行仿真分析,结果验证:所提算法能够完成电–气互联系统的气电解耦并实现多目标并行求解,从而提高系统信息私密性、实现各能源网络的分散自治.
With the background of energy internet, this paper establishes a multi-objective optimization model of integrated electric and gas system, where three objectives, e.g., the cost of energy supply, carbon emission and the smoothness of load curve, are taken into account and then an incremental piecewise linearization method is adopted to transform the nonlinear optimization model into a mixed integer linear programming model. To promote coordinated, complementary and effective use of various energy sources on the basis of disparate autonomy of each energy network, a decentralized multi-objective optimization method with decoupling between electricity and gas network is proposed, where the original multi-objective optimization problem is decomposed into two sub-problems of power grid and gas network, following by two independent optimizers to solve the sub-problems. Within each sub region, an independent optimizer is used to optimize its own sub problem using only boundary variables and virtual objective coefficients from the other interconnected region, which can be utilized for the global regulation. Finally, connecting the modified IEEE 39-node electric network and the Belgian 20-node gas network to construct a model for simulation analysis, and compare results of the proposed algorithm with that of the centralized algorithm. The simulation results verify that the proposed algorithm can accurately handle the decoupling and multi-objective parallelizing optimization of the integrated electric and gas system and achieve decentralized autonomy of energy networks, which is quite useful and valuable for improvement of system information privacy.
With the background of energy internet, this paper establishes a multi-objective optimization model of integrated electric and gas system, where three objectives, e.g., the cost of energy supply, carbon emission and the smoothness of load curve, are taken into account and then an incremental piecewise linearization method is adopted to transform the nonlinear optimization model into a mixed integer linear programming model. To promote coordinated, complementary and effective use of various energy sources on the basis of disparate autonomy of each energy network, a decentralized multi-objective optimization method with decoupling between electricity and gas network is proposed, where the original multi-objective optimization problem is decomposed into two sub-problems of power grid and gas network, following by two independent optimizers to solve the sub-problems. Within each sub region, an independent optimizer is used to optimize its own sub problem using only boundary variables and virtual objective coefficients from the other interconnected region, which can be utilized for the global regulation. Finally, connecting the modified IEEE 39-node electric network and the Belgian 20-node gas network to construct a model for simulation analysis, and compare results of the proposed algorithm with that of the centralized algorithm. The simulation results verify that the proposed algorithm can accurately handle the decoupling and multi-objective parallelizing optimization of the integrated electric and gas system and achieve decentralized autonomy of energy networks, which is quite useful and valuable for improvement of system information privacy.
引文
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[11]GUANDALINI G,CAMPANARI S,ROMANO M C.Power-to-gas plants and gas turbines for improved wind energy dispatch ability:energy and economic assessment.Applied Energy,2015,147:117-130.
[12]WEI Zhinong,ZHANG Side,SUN Guoqiang,et al.Power-to-gas considered peak load shifting research for integrated electricity and natural-gas energy systems.Proceedings of the CSEE,2017,37(16):4601-4609,4885.(卫志农,张思德,孙国强,等.计及电转气的电-气互联综合能源系统削峰填谷研究.中国电机工程学报,2017,37(16):4601-4609,4885.)
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[14]ZHOU Ming,ZHAI Junyi,REN Jianwen,et al.A decentralized coordinated dispatch approach for interconnected power grid with wind power via HVDC tie-line.Power System Technology,2017,41(5):1428-1434.(周明,翟俊义,任建文,等.含风电并网的直流互联电网分散协调调度方法.电网技术,2017,41(5):1428-1434.)
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[16]CONEJO A J,NOGALES F J,PRIETO F J.A decomposition procedure based on approximate Newton directions.Mathematical Programming,2002,93(3):495-515.
[17]BOYD S,PARIKH N,CHU E,et al.Distributed optimization and statistical learning via the alternating direction method of multipliers.Foundations&Trends in Machine Learning,2011,3(1):1-122.
[18]LOSI A,RUSSO M.On the application of the auxiliary problem principle.Journal of Optimization Theory&Applications,2003,117(2):377-396.
[19]YAN W,WEN L,Li W,et al.Decomposition-coordination interior point method and its application to multi-area optimal reactive power flow.International Journal of Electrical Power&Energy Systems,2011,33(1):55-60.
[20]WANG Chaoqun,WEI Hua,WU Siyuan,et al.Comparative analysis of seven decomposition and coordination algorithms for optimal power flow.Automation of Electric Power Systems,2016,40(6):49-57.(汪超群,韦化,吴思缘,等.七种最优潮流分解协调算法的性能比较.电力系统自动化,2016,40(6):49-57.)
[21]QU Kaiping,HUANG Linni,YU Tao,et al.Decentralized dispatch of multi-area integrated energy systems with carbon trading.Proceedings of the CSEE,2018,38(3):697-707.(瞿凯平,黄琳妮,余涛,等.碳交易机制下多区域综合能源系统的分散调度.中国电机工程学报,2018,38(3):697-707.)
[22]HU Guoqiang,HE Renmu.Model and algorithm of multi-objective fuzzy optimal scheduling for cascaded hydroelectric power plant.Transactions of China Electrotechnical Society,2007,22(1):154-158.(胡国强,贺仁睦.梯级水电站多目标模糊优化调度模型及其求解方法.电工技术学报,2007,22(1):154-158.)
[23]MUNOZ J,JIMENEZ-REDONDO N,PEREZ-RUIZ J,et al.Natural gas network modeling for power systems reliability studies.Ech Conference.Bologna,Italy:IEEE,2003:1-8.
[2]TIAN Shiming,LUAN Wenpeng,ZHANG Dongxia,et al.Technical forms and key technologies on energy internet.Proceedings of the C-SEE,2015,35(14):3482-3494.(田世明,栾文鹏,张东霞,等.能源互联网技术形态与关键技术.中国电机工程学报,2015,35(14):3482-3494.)
[3]ZENG Ming,YANG Yongqi,LI Yuanfei,et al.The preliminary research for key operation mode and technologies of electrical power system with renewable Energy sources under energy internet.Proceedings of the CSEE,2016,36(3):681-691.(曾鸣,杨雍琦,李源非,等.能源互联网背景下新能源电力系统运营模式及关键技术初探.中国电机工程学报,2016,36(3):681-691.)
[4]AI Qian,HAO Ran.Key technologies and challenges for multienergy complementarity and optimization of integrated energy system.Automation of Electric Power Systems,2018,42(4):2-10.(艾芊,郝然.多能互补、集成优化能源系统关键技术及挑战.电力系统自动化,2018,42(4):2-10.)
[5]AN S,LI Q,GEDRA T W.Natural gas and electricity optimal power flow.Transmission and Distribution Conference and Exposition.Dallas,USA:IEEE,2003:138-143.
[6]WOLF D D,SMEERS Y.The Gas transmission problem solved by an extension of the simplex algorithm.The Gas Transmission Science,2000,46(11):1454-1465.
[7]CORREA-POSADA C M,SANCHEZ-MARTIN P.Integrated power and natural gas model for energy adequacy in short-term operation.IEEE Transactions on Power Systems,2015,30(6):3347-3355.
[8]SUN Guoqiang,CHEN Shuang,WEI Zhinong,et al.Probabilistic optimal power flow of combined nature gas and electric system considering correlation.Automation of Electric Power Systems,2015,39(21):11-17.(孙国强,陈霜,卫志农,等.计及相关性的电-气互联系统概率最优潮流.电力系统自动化,2015,39(21):11-17.)
[9]CHAUDRY M,JENKINS N,STRBAC G.Multi-time period combined gas and electricity network optimization.Electric Power Systems Research,2008,78(7):1265-1279.
[10]FANG J K,ZENG Q,AI X M,et al.Dynamic optimal energy flow in the integrated natural gas and electrical power systems.IEEE Transactions on Sustainable Energy,2018,9(1):188-198.
[11]GUANDALINI G,CAMPANARI S,ROMANO M C.Power-to-gas plants and gas turbines for improved wind energy dispatch ability:energy and economic assessment.Applied Energy,2015,147:117-130.
[12]WEI Zhinong,ZHANG Side,SUN Guoqiang,et al.Power-to-gas considered peak load shifting research for integrated electricity and natural-gas energy systems.Proceedings of the CSEE,2017,37(16):4601-4609,4885.(卫志农,张思德,孙国强,等.计及电转气的电-气互联综合能源系统削峰填谷研究.中国电机工程学报,2017,37(16):4601-4609,4885.)
[13]LIU Baoying,YANG Rengang.Muti-subarea parallel reactive power optimization based on APP.Proceedings of the CSEE,2009,29(7):47-51.(刘宝英,杨仁刚.采用辅助问题原理的多分区并行无功优化算法.中国电机工程学报,2009,29(7):47-51.)
[14]ZHOU Ming,ZHAI Junyi,REN Jianwen,et al.A decentralized coordinated dispatch approach for interconnected power grid with wind power via HVDC tie-line.Power System Technology,2017,41(5):1428-1434.(周明,翟俊义,任建文,等.含风电并网的直流互联电网分散协调调度方法.电网技术,2017,41(5):1428-1434.)
[15]WEN Yunfeng,GUO Chuangxin,GUO Jianbo,et al.Coordinated decentralized risk-based dispatch of multi-area interconnected power systems.Proceedings of the CSEE,2015,35(14):3724-3733.(文云峰,郭创新,郭剑波,等.多区互联电力系统的分散协调风险调度方法.中国电机工程学报,2015,35(14):3724-3733.)
[16]CONEJO A J,NOGALES F J,PRIETO F J.A decomposition procedure based on approximate Newton directions.Mathematical Programming,2002,93(3):495-515.
[17]BOYD S,PARIKH N,CHU E,et al.Distributed optimization and statistical learning via the alternating direction method of multipliers.Foundations&Trends in Machine Learning,2011,3(1):1-122.
[18]LOSI A,RUSSO M.On the application of the auxiliary problem principle.Journal of Optimization Theory&Applications,2003,117(2):377-396.
[19]YAN W,WEN L,Li W,et al.Decomposition-coordination interior point method and its application to multi-area optimal reactive power flow.International Journal of Electrical Power&Energy Systems,2011,33(1):55-60.
[20]WANG Chaoqun,WEI Hua,WU Siyuan,et al.Comparative analysis of seven decomposition and coordination algorithms for optimal power flow.Automation of Electric Power Systems,2016,40(6):49-57.(汪超群,韦化,吴思缘,等.七种最优潮流分解协调算法的性能比较.电力系统自动化,2016,40(6):49-57.)
[21]QU Kaiping,HUANG Linni,YU Tao,et al.Decentralized dispatch of multi-area integrated energy systems with carbon trading.Proceedings of the CSEE,2018,38(3):697-707.(瞿凯平,黄琳妮,余涛,等.碳交易机制下多区域综合能源系统的分散调度.中国电机工程学报,2018,38(3):697-707.)
[22]HU Guoqiang,HE Renmu.Model and algorithm of multi-objective fuzzy optimal scheduling for cascaded hydroelectric power plant.Transactions of China Electrotechnical Society,2007,22(1):154-158.(胡国强,贺仁睦.梯级水电站多目标模糊优化调度模型及其求解方法.电工技术学报,2007,22(1):154-158.)
[23]MUNOZ J,JIMENEZ-REDONDO N,PEREZ-RUIZ J,et al.Natural gas network modeling for power systems reliability studies.Ech Conference.Bologna,Italy:IEEE,2003:1-8.