考虑电、气、热耦合性及随机性的IES-CCHP综合收益模型
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摘要
为鼓励综合能源系统背景下更多的联供系统积极参与进来,针对该系统中电力、天然气和热力系统之间的交互影响及其不确定因素,考虑它们之间的耦合性及随机性,建立冷热电三联供综合收益模型。本文提出一种基于Nataf变换的自修正粒子群优化算法求解模型,采用Nataf变换的多点估计法将随机量转换,生成满足耦合关系并接近实际值的样本矩阵,动态地修正粒子惯性权重。算例分析表明,计及耦合性和随机性的联供系统综合收益更大;所提出的算法大大降低了随机性且有较强的全局搜索能力。
Uncertain factors are gradually increasing with the frequent interactions between power,natural gas and thermal system in the context of integrated energy system(IES). Considering the coupling and randomness therein,a comprehensive profit model,i.e.,integrated energy system-combined cooling,heating and power(IES-CCHP),is estab-lished to encourage more CCHPs to participate in energy dispatching actively. In this paper,a Nataf transformation-based self-correction particle swarm optimization(PSO)algorithm is proposed to solve this model. First,a multi-pointestimation method based on Nataf transformation is adopted to generate a sample matrix,which satisfies the coupling relationship and is close to the actual values. Then,the dynamic correction of the inertia weights of particles is calculated.A numerical example shows that IES-CCHP can generate more comprehensive profit in consideration of the couplingand randomness characteristics;Moreover,the proposed algorithm reduces the randomness obviously,and has a strongglobal search capability.
Uncertain factors are gradually increasing with the frequent interactions between power,natural gas and thermal system in the context of integrated energy system(IES). Considering the coupling and randomness therein,a comprehensive profit model,i.e.,integrated energy system-combined cooling,heating and power(IES-CCHP),is estab-lished to encourage more CCHPs to participate in energy dispatching actively. In this paper,a Nataf transformation-based self-correction particle swarm optimization(PSO)algorithm is proposed to solve this model. First,a multi-pointestimation method based on Nataf transformation is adopted to generate a sample matrix,which satisfies the coupling relationship and is close to the actual values. Then,the dynamic correction of the inertia weights of particles is calculated.A numerical example shows that IES-CCHP can generate more comprehensive profit in consideration of the couplingand randomness characteristics;Moreover,the proposed algorithm reduces the randomness obviously,and has a strongglobal search capability.
引文
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[13]周任军,闵雄帮,童小娇,等(Zhou Renjun,Min Xiongbang,Tong Xiaojiao,et al).电力环保经济调度矩不确定分布鲁棒优化方法(Distributional robust optimization under moment uncertainty of environmental and economic dispatch for power system)[J].中国电机工程学报(Proceedings of the CSEE),2015,5(13):3248-3256.
[14]韩海腾,高山,吴晨,等(Han Haiteng,Gao Shan,Wu Chen,et al).基于Nataf变换的电网不确定性多点估计法(Uncertain power flow solved by multi-point estimate method based on Nataf transformation)[J].电力系统自动化(Automation of Electric Power Systems),2015,39(7):28-34.
[15]王威,韩学山,李保银(Wang Wei,Han Xueshan,Li Baoyin).基于机会约束规划的含风机配电网重构(Reconfiguration of distribution network with wind turbines based on chance-constrained programming)[J].电力系统及其自动化学报(Proceedings of the CSU-EPSA),2014,26(5):23-26.
[16]杨欢,邹斌(Yang Huan,Zou Bin).含相关性随机变量的概率潮流三点估计法(A three-point estimate method for solving probabilistic power flow problems with correlated random variables)[J].电力系统自动化(Automation of Electric Power Systems),2012,36(15):51-56.
[17]Pehlivanoglu Y V.A new particle swarm optimization method enhanced with a periodic mutation strategy and neural networks[J].IEEE Trans on Evolutionary Computation,2013,17(3):436-452.
[18]唐贤伦,程祥,汪斌全(Tang Xianlun,Cheng Xiang,Wang Binquan).采用多Agent混沌粒子群算法的配电网重构(Distribution network reconfiguration adopting chaos particle swarm algorithm of multi-agent system)[J].电力系统及其自动化学报(Proceedings of the CSU-EPSA),2015,27(3):17-23.
[19]刘静,罗先觉(Liu Jing,Luo Xianjue).采用多目标随机黑洞粒子群优化算法的环境经济发电调度(Environmental economic dispatching adopting multiobjective random black-hole particle swarm optimization algorithm)[J].中国电机工程学报(Proceedings of the CSEE),2010,30(34):105-111.
[20]周任军,李绍金,陈瑞先,等(Zhou Renjun,Li Shaojin,Chen Ruixian,et al).采用模糊自修正粒子群算法的碳排放权交易冷热电多目标调度(Combined cool and heat and power multi-objective scheduling considering carbon emissions trading using algorithm of fuzzy self-correction particle swarm optimization)[J].中国电机工程学报(Proceedings of the CSEE),2014,34(34):6119-6126.
[2]贾宏杰,王丹,徐宪东,等(Jia Hongjie,Wang Dan,Xu Xiandong,et al).区域综合能源系统若干问题研究(Research on some key problems related to integrated energy systems)[J].电力系统自动化(Automation of Electric Power Systems),2015,39(7):198-207.
[3]Stanislav P,Bryan K,Tihomir M.Smart grids better with integrated energy system[C]//IEEE Electrical Power&Energy Conference.Montreal,Canada,2009.
[4]吴建中(Wu Jianzhong).欧洲综合能源系统发展的驱动与现状(Drivers and state-of-the-art of integrated energy systems in Europe)[J].电力系统自动化(Automation of Electric Power Systems),2016,40(5):1-7.
[5]王伟亮,王丹,贾宏杰,等(Wang Weiliang,Wang Dan,Jia Hongjie,et al).能源互联网背景下的典型区域综合能源系统稳态分析研究综述(Review of steady-state analysis of typical regional integrated energy system under the background of energy internet)[J].中国电机工程学报(Proceedings of the CSEE),2016,36(12):3292-3305.
[6]兰立雄,刘力卿,米增强(Lan Lixiong,Liu Liqing,Mi Zengqiang).冷电联供系统的多目标运行优化(Optimal operation of combined cooling and power supply system)[J].电力系统及其自动化学报(Proceedings of the CSUEPSA),2016,28(5):62-68.
[7]王珺,顾伟,陆帅,等(Wang Jun,Gu Wei,Lu Shuai,et al).结合热网模型的多区域综合能源系统协同规划(Coordinated planning of multi-district integrated energy system combining heating network model)[J].电力系统自动化(Automation of Electric Power Systems),2016,40(15):17-24.
[8]刘方,杨秀,黄海涛,等(Liu Fang,Yang Xiu,Huang Haitao,et al).含热电联产热电解耦运行方式下的微网能量综合优化(Energy comprehensive optimization of micro-grid including CHP with thermoelectric decoupling operation mode)[J].电力系统及其自动化学报(Proceedings of the CSU-EPSA),2016,28(1):51-57.
[9]Sahin C,Shahidehpour M,Erkmen I.Generation risk assessment in volatile conditions with wind,hydro,and natural gas units[J].Applied Energy,2012,96:4-11.
[10]Alabdulwahab A,Abusorrah A,Zhang Xiaoping,et al.Coordination of interdependent natural gas and stochastic day-ahead scheduling electricity infrastructures for firming the variability of wind energy in stochastic day-ahead scheduling[J].IEEE Trans on Sustainable Energy,2015,6(2):606-615.
[11]王英瑞,曾博,郭经,等(Wang Yingrui,Zeng Bo,Guo Jing,et al).电-热-气综合能源系统多能流计算方法(Multi-energy flow calculation method for integrated energy system containing electricity,heat and gas)[J].电网技术(Power System Technology),2016,40(10):2942-2950.
[12]徐宪东,贾宏杰,靳小龙,等(Xu Xiandong,Jia Hongjie,Jin Xiaolong,et al).区域综合能源系统电/气/热混合潮流算法研究(Study on hybrid heat-gas-power flow algorithm for integrated community energy system)[J].中国电机工程学报(Proceedings of the CSEE),2015,35(14):3634-3642.
[13]周任军,闵雄帮,童小娇,等(Zhou Renjun,Min Xiongbang,Tong Xiaojiao,et al).电力环保经济调度矩不确定分布鲁棒优化方法(Distributional robust optimization under moment uncertainty of environmental and economic dispatch for power system)[J].中国电机工程学报(Proceedings of the CSEE),2015,5(13):3248-3256.
[14]韩海腾,高山,吴晨,等(Han Haiteng,Gao Shan,Wu Chen,et al).基于Nataf变换的电网不确定性多点估计法(Uncertain power flow solved by multi-point estimate method based on Nataf transformation)[J].电力系统自动化(Automation of Electric Power Systems),2015,39(7):28-34.
[15]王威,韩学山,李保银(Wang Wei,Han Xueshan,Li Baoyin).基于机会约束规划的含风机配电网重构(Reconfiguration of distribution network with wind turbines based on chance-constrained programming)[J].电力系统及其自动化学报(Proceedings of the CSU-EPSA),2014,26(5):23-26.
[16]杨欢,邹斌(Yang Huan,Zou Bin).含相关性随机变量的概率潮流三点估计法(A three-point estimate method for solving probabilistic power flow problems with correlated random variables)[J].电力系统自动化(Automation of Electric Power Systems),2012,36(15):51-56.
[17]Pehlivanoglu Y V.A new particle swarm optimization method enhanced with a periodic mutation strategy and neural networks[J].IEEE Trans on Evolutionary Computation,2013,17(3):436-452.
[18]唐贤伦,程祥,汪斌全(Tang Xianlun,Cheng Xiang,Wang Binquan).采用多Agent混沌粒子群算法的配电网重构(Distribution network reconfiguration adopting chaos particle swarm algorithm of multi-agent system)[J].电力系统及其自动化学报(Proceedings of the CSU-EPSA),2015,27(3):17-23.
[19]刘静,罗先觉(Liu Jing,Luo Xianjue).采用多目标随机黑洞粒子群优化算法的环境经济发电调度(Environmental economic dispatching adopting multiobjective random black-hole particle swarm optimization algorithm)[J].中国电机工程学报(Proceedings of the CSEE),2010,30(34):105-111.
[20]周任军,李绍金,陈瑞先,等(Zhou Renjun,Li Shaojin,Chen Ruixian,et al).采用模糊自修正粒子群算法的碳排放权交易冷热电多目标调度(Combined cool and heat and power multi-objective scheduling considering carbon emissions trading using algorithm of fuzzy self-correction particle swarm optimization)[J].中国电机工程学报(Proceedings of the CSEE),2014,34(34):6119-6126.