基于粒子群算法的输电能力经济性优化
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摘要
有效评估电力系统输电能力在如今互联的电力系统运行和规划中越来越重要,基于此提出了一种计及经济性并同时考虑电力市场调度的输电能力评估方法,将其定义为输电能力的经济性评估。首先构建一个对输电能力进行经济性评估的多目标优化数学模型,并利用粒子群算法求解该模型。然后在经典的3机9节点系统上进行仿真验证,证明了所提出的方法通过粒子群算法使得互连系统的源、荷区域之间的传输功率最大化,负载水平本身即为优化模型的边界条件,且能够满足系统安全稳定性的约束,该方法适用于不同拓扑、不同负载水平的网络。优化结果有助于电力市场的系统运营商和规划人员正确评估互连区域市场与电价对最大输电能力的影响。
It is more and more important to effectively evaluate power transfer capacity of the power system in current interconnected power system operation and planning. This paper presents a kind of evaluation method for power transfer capacity considering economy and electricity market dispatching which is defined as economy evaluation of power transfer capacity(EETC). It firstly constructs a multi-objective optimal mathematical model for EETC and uses particle swarm optimization(PSO) algorithm to solve this model. Then it makes simulation for verification on the classical 3-machine 9-bus system and proves the proposed method can maximize transfer power between the source area and the load area of the interconnected system by using PSO algorithm. Meanwhile, load level is the boundary condition of the optimal model which is able to satisfy constrain of safety and stability of the system. This method is suitable for networks with different topologies and load levels. The optimal results are beneficial for system operators and planners of the electricity market to correctly evaluation effects of the interconnected regional market and electricity price on the maximum power transfer capacity.
It is more and more important to effectively evaluate power transfer capacity of the power system in current interconnected power system operation and planning. This paper presents a kind of evaluation method for power transfer capacity considering economy and electricity market dispatching which is defined as economy evaluation of power transfer capacity(EETC). It firstly constructs a multi-objective optimal mathematical model for EETC and uses particle swarm optimization(PSO) algorithm to solve this model. Then it makes simulation for verification on the classical 3-machine 9-bus system and proves the proposed method can maximize transfer power between the source area and the load area of the interconnected system by using PSO algorithm. Meanwhile, load level is the boundary condition of the optimal model which is able to satisfy constrain of safety and stability of the system. This method is suitable for networks with different topologies and load levels. The optimal results are beneficial for system operators and planners of the electricity market to correctly evaluation effects of the interconnected regional market and electricity price on the maximum power transfer capacity.
引文
[1] 范京艺,毛安家,刘岩,等.基于负荷和环境温度曲线的输电断面短时过载能力分析[J]. 电力系统保护与控制,2018,46(1):116-121. FAN Jingyi,MAO Anjia,LIU Yan,et al. Analysis of the short-time overload capability of the transmission section based on the load and ambient temperature curve[J]. Power System Protection and Control,2018,46(1):116-121.
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[3] OU Y, SINGH C. Assessment of available transfer capability and margins[J]. IEEE Power Engineering Review, 2002, 22(5):69-69.
[4] 陈展,张利民,赵海成,等.基于主从神经网络的短期电力负荷预测研究[J]. 陕西电力,2014,42(7):57-60. CHEN Zhan,ZHANG Limin,ZHAO Haicheng,et al.Study on short term power load forecasting based on master-slave neural network[J]. Shaanxi Electric Power,2014,42(7):57-60.
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[7] 赖文海,陈贤阳,明国锋,等. 基于双种群小生境差分进化算法的动态经济调度[J]. 广东电力,2016,29(7):83-87,92. LAI Wenhai, CHEN Xianyang, MING Guofeng, et al. Dynamic economic dispatching based on dual population niche differential evolution algorithm[J]. Guangdong Electric Power,2016,29(7):83-87,92.
[8] 蔡妙妆,李慧,杜锦阳,等. 改进纵横交叉算法在电力系统环境经济调度方面的研究[J]. 广东电力,2017,30(1):46-52. CAI Miaozhuang, LI Hui, DU Jinyang, et al. Research on improved vertical and horizontal intersection algorithm in power system environment and economy dispatching[J]. Guangdong Electric Power,2017,30(1):46-52.
[9] 林艺城,李锦焙,孟安波,等. 基于改进差分纵横交叉算法的多区域动态经济调度[J]. 广东电力,2017,30(5):69-76. LIN Yicheng, LI Jinpei, MENG Anbo, et al. Multi-area Dynamic economic dispatching based on improved differential evolution with crisscrossed optimization algorithm[J]. Guangdong Electric Power,2017,30(5):69-76.
[10] 金华征. 考虑市场环境的多目标输电网优化规划研究[D]. 上海:上海交通大学, 2007.
[11] 李卫星, 李志民, 郭志忠,等. 考虑经济性收益最大的可用输电能力计算[J]. 电力系统自动化, 2004, 28(20):7-11. LI Weixing,LI Zhimin,GUO Zhizhong,et al.Available transfer capability calculation based on maximizing system benefit[J]. Automation of Electric Power Systems,2004,28(20):7-11.
[12] 徐劭翔, 苗世洪, 周良松. 跨区域互联电网的可用输电能力计算方法[J]. 电力系统自动化, 2017,41(15):74-80. XU Shaoxiang, MIAO Shihong, ZHOU Liangsong. Calculation method of available transfer capability for cross-regional interconnected power grid[J]. Automation of Electric Power Systems, 2017, 41(15): 74-80.
[13] 陈厚合, 何旭, 姜涛, 等. 计及可中断负荷的电力系统可用输电能力计算[J]. 电力系统自动化, 2017, 41(15): 81-87. CHEN Houhe, HE Xu, JIANG Tao, et al. Available transfer capability calculation of power systems considering interruptible load[J]. Automation of Electric Power Systems, 2017, 41(15):81-87.
[14] 韩通, 陈艳波, 韩子娇, 等. 基于最优潮流的含VSC-HVDC交直流系统最大输电能力计算[J]. 电力系统自动化, 2016, 40(17): 113-121. HAN Tong, CHEN Yanbo, HAN Zijiao, et al. Optimal power flow based total transfer capability calculation for AC/DC system with VSC-HVDC[J]. Automation of Electric Power Systems, 2016, 40(17): 113-121.
[15] YANG Y, BAO M, DING Y, et al. Review of information disclosure in different electricity markets[J]. Energies, 2018, 11(12): 3424.
[16] BHATTACHARYA K, BOLLEN M H J, DAALDER J E. Operation of Restructured Power Systems[M]. Boston: Kluwer Academic Pub, 2001.
[17] GAN D, LUO X, BOURCIER D V, et al. Min–max transfer capabilities of transmission interfaces[J]. International Journal of Electrical Power & Energy Systems, 2003, 25(5):347-353.
[18] CONEJO A J, AGUADO J A. Multi-area coordinated decentralized DC optimal power flow[J]. IEEE Transactions on Power Systems, 1998, 13(4):1272-1278.
[19] 唐佳, 王丹, 贾宏杰, 等. 基于元模型辅助粒子群算法的主动配电网最优经济运行[J]. 电力系统自动化, 2018, 42(4): 95-103. TANG Jia, WANG Dan, JIA Hongjie, et al. Optimal economic operation of active distribution networks based on hybrid algorithm of surrogate model and particle swarm optimization[J]. Automation of Electric Power Systems, 2018, 42(4): 95-103.
[20] 韩鹏, 李银红, 何璇, 等. 结合量子粒子群算法的光伏多峰最大功率点跟踪改进方法[J]. 电力系统自动化, 2016, 40(23): 101-108. HAN Peng, LI Yinhong, HE Xuan, et al. Improved maximum power point tracking method for photovoltaic multi-peak based on quantum-behaved particle swarm optimization algorithm[J]. Automation of Electric Power Systems, 2016, 40(23): 101-108.项目简介:申请单位冀北张家口供电公司经济技术研究所项目名称考虑新能源出力不确定性因素的电网线路充裕度评估项目概述项目考虑新能源出力等不确定性因素研究并提出电网线路充裕度的评估方法;在此基础上,构建电网线路充裕度的工程实用指标,并考虑电网的不同发展阶段,给出线路充裕度指标的参考范围。主要创新点提出考虑不确定性因素的电网线路充裕度评价方法,提出电网线路充裕度的工程实用指标,并考虑电网的不同发展阶段,给出线路充裕度指标的参考范围。
[2] 罗钢. 电网可用输电能力的计算方法研究[D]. 武汉:华中科技大学, 2014.
[3] OU Y, SINGH C. Assessment of available transfer capability and margins[J]. IEEE Power Engineering Review, 2002, 22(5):69-69.
[4] 陈展,张利民,赵海成,等.基于主从神经网络的短期电力负荷预测研究[J]. 陕西电力,2014,42(7):57-60. CHEN Zhan,ZHANG Limin,ZHAO Haicheng,et al.Study on short term power load forecasting based on master-slave neural network[J]. Shaanxi Electric Power,2014,42(7):57-60.
[5] BRESESTI P,LUCARELLA D,MARANNINO P,et al. An OPF-based procedure for fast TTC analyses[C]//Power Engineering Society Summer Meeting. Piscataway:IEEE, 2005:1504-1509.
[6] BHESDADIYA R H,PATEL R M. Available transfer capability calculation using deterministic methods: a case study of Indian power system[C]//2016 International Conference on Electrical, Electronics and Optimization Techniques (ICEEOT). Piscataway: IEEE, 2016: 2261-2264.
[7] 赖文海,陈贤阳,明国锋,等. 基于双种群小生境差分进化算法的动态经济调度[J]. 广东电力,2016,29(7):83-87,92. LAI Wenhai, CHEN Xianyang, MING Guofeng, et al. Dynamic economic dispatching based on dual population niche differential evolution algorithm[J]. Guangdong Electric Power,2016,29(7):83-87,92.
[8] 蔡妙妆,李慧,杜锦阳,等. 改进纵横交叉算法在电力系统环境经济调度方面的研究[J]. 广东电力,2017,30(1):46-52. CAI Miaozhuang, LI Hui, DU Jinyang, et al. Research on improved vertical and horizontal intersection algorithm in power system environment and economy dispatching[J]. Guangdong Electric Power,2017,30(1):46-52.
[9] 林艺城,李锦焙,孟安波,等. 基于改进差分纵横交叉算法的多区域动态经济调度[J]. 广东电力,2017,30(5):69-76. LIN Yicheng, LI Jinpei, MENG Anbo, et al. Multi-area Dynamic economic dispatching based on improved differential evolution with crisscrossed optimization algorithm[J]. Guangdong Electric Power,2017,30(5):69-76.
[10] 金华征. 考虑市场环境的多目标输电网优化规划研究[D]. 上海:上海交通大学, 2007.
[11] 李卫星, 李志民, 郭志忠,等. 考虑经济性收益最大的可用输电能力计算[J]. 电力系统自动化, 2004, 28(20):7-11. LI Weixing,LI Zhimin,GUO Zhizhong,et al.Available transfer capability calculation based on maximizing system benefit[J]. Automation of Electric Power Systems,2004,28(20):7-11.
[12] 徐劭翔, 苗世洪, 周良松. 跨区域互联电网的可用输电能力计算方法[J]. 电力系统自动化, 2017,41(15):74-80. XU Shaoxiang, MIAO Shihong, ZHOU Liangsong. Calculation method of available transfer capability for cross-regional interconnected power grid[J]. Automation of Electric Power Systems, 2017, 41(15): 74-80.
[13] 陈厚合, 何旭, 姜涛, 等. 计及可中断负荷的电力系统可用输电能力计算[J]. 电力系统自动化, 2017, 41(15): 81-87. CHEN Houhe, HE Xu, JIANG Tao, et al. Available transfer capability calculation of power systems considering interruptible load[J]. Automation of Electric Power Systems, 2017, 41(15):81-87.
[14] 韩通, 陈艳波, 韩子娇, 等. 基于最优潮流的含VSC-HVDC交直流系统最大输电能力计算[J]. 电力系统自动化, 2016, 40(17): 113-121. HAN Tong, CHEN Yanbo, HAN Zijiao, et al. Optimal power flow based total transfer capability calculation for AC/DC system with VSC-HVDC[J]. Automation of Electric Power Systems, 2016, 40(17): 113-121.
[15] YANG Y, BAO M, DING Y, et al. Review of information disclosure in different electricity markets[J]. Energies, 2018, 11(12): 3424.
[16] BHATTACHARYA K, BOLLEN M H J, DAALDER J E. Operation of Restructured Power Systems[M]. Boston: Kluwer Academic Pub, 2001.
[17] GAN D, LUO X, BOURCIER D V, et al. Min–max transfer capabilities of transmission interfaces[J]. International Journal of Electrical Power & Energy Systems, 2003, 25(5):347-353.
[18] CONEJO A J, AGUADO J A. Multi-area coordinated decentralized DC optimal power flow[J]. IEEE Transactions on Power Systems, 1998, 13(4):1272-1278.
[19] 唐佳, 王丹, 贾宏杰, 等. 基于元模型辅助粒子群算法的主动配电网最优经济运行[J]. 电力系统自动化, 2018, 42(4): 95-103. TANG Jia, WANG Dan, JIA Hongjie, et al. Optimal economic operation of active distribution networks based on hybrid algorithm of surrogate model and particle swarm optimization[J]. Automation of Electric Power Systems, 2018, 42(4): 95-103.
[20] 韩鹏, 李银红, 何璇, 等. 结合量子粒子群算法的光伏多峰最大功率点跟踪改进方法[J]. 电力系统自动化, 2016, 40(23): 101-108. HAN Peng, LI Yinhong, HE Xuan, et al. Improved maximum power point tracking method for photovoltaic multi-peak based on quantum-behaved particle swarm optimization algorithm[J]. Automation of Electric Power Systems, 2016, 40(23): 101-108.项目简介:申请单位冀北张家口供电公司经济技术研究所项目名称考虑新能源出力不确定性因素的电网线路充裕度评估项目概述项目考虑新能源出力等不确定性因素研究并提出电网线路充裕度的评估方法;在此基础上,构建电网线路充裕度的工程实用指标,并考虑电网的不同发展阶段,给出线路充裕度指标的参考范围。主要创新点提出考虑不确定性因素的电网线路充裕度评价方法,提出电网线路充裕度的工程实用指标,并考虑电网的不同发展阶段,给出线路充裕度指标的参考范围。