考虑可再生能源出力概率模型和预测负荷区间模型的输电网规划方法
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摘要
针对电网规划过程中不确定因素的数学模型类型不一致的情况,提出了考虑可再生能源出力概率模型和预测负荷区间模型的输电网规划方法。首先给出了考虑区间数的扩展随机机会约束规划模型;然后建立了以投资成本最小为目标函数,以支路潮流的扩展随机机会测度作为约束条件,同时考虑随机不确定因素和区间不确定因素的输电网规划模型;采用粒子群优化算法优化规划方案,采用准蒙特卡洛模拟和改进的分支定界相结合的方法对规划方案进行安全校验。IEEE RTS-24节点系统和某实际电网的案例结果证明了所提算法的有效性和正确性。
The same type of uncertainty model is usually taken into account in the existing transmission network expansion planning(TNEP) methods considering uncertainties. But in the process of TNEP, mathematical characteristic of uncertain factors may be different. In order to solve this problem, a TNEP method considering probabilistic model of renewable energy and interval model of predicted load is put forward. Firstly, an expanded stochastic chance constrained programming model considering interval number is presented. Then, a TNEP model is constructed, which considers probabilistic model and interval model of uncertainties. This model minimizs the investment cost and subjects to the expanded stochastic chance constraint of branch power. The particle swarm optimization method is employed to optimize the planning schemes and the hybrid quasi Monte Carlo simulation and improved branch-and-bound method is adopted to check the security of the given planning schemes. The case analyses on the modified IEEE RTS-24 bus system and an actual power grid verify the effectiveness and validity of the proposed planning method.
The same type of uncertainty model is usually taken into account in the existing transmission network expansion planning(TNEP) methods considering uncertainties. But in the process of TNEP, mathematical characteristic of uncertain factors may be different. In order to solve this problem, a TNEP method considering probabilistic model of renewable energy and interval model of predicted load is put forward. Firstly, an expanded stochastic chance constrained programming model considering interval number is presented. Then, a TNEP model is constructed, which considers probabilistic model and interval model of uncertainties. This model minimizs the investment cost and subjects to the expanded stochastic chance constraint of branch power. The particle swarm optimization method is employed to optimize the planning schemes and the hybrid quasi Monte Carlo simulation and improved branch-and-bound method is adopted to check the security of the given planning schemes. The case analyses on the modified IEEE RTS-24 bus system and an actual power grid verify the effectiveness and validity of the proposed planning method.
引文
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[22]陈雁.含大规模风电场电力系统的运行与规划方法研究[D].武汉:华中科技大学,2012.Chen Yan.Study on the operation and planning of power system with large-scale wind farms[D].Wuhan:Huazhong University of Science and Technology,2012.
[2]SolarPower Europe.Global market outlook for solar power/2018-2022[R].Brussels:SolarPower Europe,2018.
[3]英国石油公司.BP世界能源统计年鉴(2018)[R].伦敦:英国石油公司,2018.
[4]全球能源互联网发展合作组织.全球能源互联网骨干网架研究(2018)[R].北京:全球能源互联网发展合作组织,2018.
[5]周孝信,陈树勇,鲁宗相,等.能源转型中我国新一代电力系统的技术特征[J].中国电机工程学报,2018,38(7):1893-1904.Zhou Xiaoxin,Chen Shuyong,Lu Zongxiang,et al.Technology features of the new generation power system in China[J].Proceedings of the CSEE,2018,38(7):1893-1904(in Chinese).
[6]Moeini A M,Abbaspour A,Fotuhi F M.Incorporating largescale distant wind farms in probabilistic transmission expansion planning-part I:theory and algorithm[J].IEEE Transactions on Power Systems,2012,27(3):1585-1593.
[7]Moeini A M,Abbaspour A,Fotuhi F M.Incorporating largescale distant wind farms in probabilistic transmission expansion planning-part II:case studies[J].IEEE Transactions on Power Systems,2012,27(3):1594-601.
[8]黄裕春,杨甲甲,文福拴,等.计及接纳间歇性电源能力的输电系统规划方法[J].电力系统自动化,2013,37(4):28-35.Huang Yuchun,Yang Jiajia,Wen Fushuan,et al.Transmission system planning considering capability of accommodating intermittent generation source[J].Automation of Electric Power Systems,2013,37(4):28-35(in Chinese).
[9]Park H,Baldick R,Morton D P.A Stochastic transmission planning model with dependent load and wind forecasts[J].IEEE Transactions on Power Systems,2015,30(6):3003-3011.
[10]Yu H,Chung C Y,Wong K P.Robust transmission network expansion planning method with Taguchi’s orthogonal array testing[J].IEEE Transactions on Power Systems,2011,26(3):1573-1580.
[11]Jabr R A.Robust transmission network expansion planning with uncertain renewable generation and loads[J].IEEETransactions on Power Systems,2013,28(4):4558-4567.
[12]陈雁,文劲宇,程时杰.电网规划中考虑风电场影响的最小切负荷量研究[J].中国电机工程学报,2012,31(34):20-27.Chen Yan,Wen Jinyu,Cheng Shijie.Minimum loadcurtailment in transmission network planning considering integrated wind farms[J].Proceedings of the CSEE,2012,31(34):20-27(in Chinese).
[13]Qin Z,Li W,Xiong X.Estimating wind speed probability distribution using kernel density method[J].Electric Power Systems Research,2011,81(12):2139-2146.
[14]Zhang L,Cheng H,Zhang S,et al.Probabilistic power flow calculation using the Johnson system and Sobol’s quasirandom numbers[J].IET Generation,Transmission&Distribution,2016,10(12):3050-3059.
[15]Chen X,Tung Y.Investigation of polynomial normal transform[J].Structural Safety,2003,25(4):423-445.
[16]Zou B,Xiao Q.Solving probabilistic optimal power flow problem using quasi Monte Carlo method and ninth-order polynomial normal transformation[J].IEEE Transactions on Power Systems,2014,29(1):300-306.
[17]Zhang S,Cheng H,Wan D,et al.Distributed generation planning in active distribution network considering demand side management and network reconfiguration[J].Applied Energy,2018,228:1921-1936.
[18]Wu P,Cheng H,Xing J.The interval minimum load cutting problem in the process of transmission expansion planning considering uncertainty in demand[J].IEEE Transactions on Power Systems,2008,23(3):1497-1506.
[19]Kennedy J,Eberhart R.Particle swarm optimization[C]//IEEEInternational Conference on Neural Networks.New York:IEEE,1995:1942-1948.
[20]Subcommittee P M.IEEE Reliability Test System[J].IEEETransactions on Power Apparatus&Systems,1979,PAS-98(6):2047-2054.
[21]秦志龙,李文沅,熊小伏.含具有风速相关性风电场的发输电系统可靠性评估[J].电力系统保护与控制,2013,41(20):27-33.Qin Zhilong,Li Wenyuan,Xiong Xiaofu.Reliability assessment of composite generation and transmission systems with wind farms considering wind speed correlations[J].Power System Protection and Control,2013,41(20):27-33(in Chinese).
[22]陈雁.含大规模风电场电力系统的运行与规划方法研究[D].武汉:华中科技大学,2012.Chen Yan.Study on the operation and planning of power system with large-scale wind farms[D].Wuhan:Huazhong University of Science and Technology,2012.