变电站容量和DG置信容量概率规划
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摘要
针对基于主变"N-1"安全准则或给定容量比确定变电站容量存在的问题,采用概率规划方法,基于总费用最小建立了涉及DG的变电站容量优化简化模型:目标函数考虑了变电站容量投资和停电损失费用;约束为相关配电网规划导则中推荐的主变容量及其组合。其中,通过多场景概率分析法建立了DG的多状态出力模型;提出了较小供电区域内一般仅需对不同类型DG状态进行组合来考虑分布式电源出力的相关性。考虑到实际变电容量的离散性,模型采用枚举法进行求解。基于模型求解获得的变电站优化容量,定义了两类DG变电置信容量,将传统的DG变电置信容量评估转换成了基于变电站优化容量的DG变电置信容量计算。算例表明了概率规划对于变电站容量选择的意义以及DG对变电站容量的替代作用。
To solve the problem of determining substation capacities based on main transformer "N–1" safety guidelines or given capacity-load ratio, a simplified model of substation capacity optimization involving DG is established based on minimum total cost by using a probabilistic planning method. The objective function considers the investment of substation capacity and the cost of outage loss. Constrains include the recommended capacity of main transformer and its combination in relevant distribution network planning guidelines. The multi-state output model of DGs is established by multi-scenario probability analysis method, and the correlation of DGs output is considered only by combining different types of DGs states in a small power supply area. The model is solved by enumeration method considering the discreteness of the actual transformer capacity. Two types of DG substation capacity credit are defined based on the optimal capacity of substation obtained by solving the model, therefore the traditional evaluation problem is transformed into the calculation of DG substation capacity credit based on the optimal substation capacity. The numerical examples show the significance of probabilistic substation capacity planning and the substitution effect of DGs for substation capacities.
To solve the problem of determining substation capacities based on main transformer "N–1" safety guidelines or given capacity-load ratio, a simplified model of substation capacity optimization involving DG is established based on minimum total cost by using a probabilistic planning method. The objective function considers the investment of substation capacity and the cost of outage loss. Constrains include the recommended capacity of main transformer and its combination in relevant distribution network planning guidelines. The multi-state output model of DGs is established by multi-scenario probability analysis method, and the correlation of DGs output is considered only by combining different types of DGs states in a small power supply area. The model is solved by enumeration method considering the discreteness of the actual transformer capacity. Two types of DG substation capacity credit are defined based on the optimal capacity of substation obtained by solving the model, therefore the traditional evaluation problem is transformed into the calculation of DG substation capacity credit based on the optimal substation capacity. The numerical examples show the significance of probabilistic substation capacity planning and the substitution effect of DGs for substation capacities.
引文
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[3]霍凯龙,王主丁,张代红,等.大规模变电站多阶段规划优化实用方法[J].电力系统及其自动化学报,2017,29(5):122-128.Huo Kailong,Wang Zhuding,Zhang Daihong,et al.Practical method of multi-stage planning optimization for large-scale substation[J].Proceedings of the CSU-EPSA,2017,29(5):122-128(in Chinese).
[4]胡玉生,翟进乾,张辉,等.变电站规划优化解析模型和简化算法[J].智慧电力,2018,46(1):63-70.Hu Yusheng,Zhai Jinqian,Zhang Hui,et al.Analytical models and simplified algorithms for substation optimization[J].Smart Power,2018,46(1):63-70(in Chinese).
[5]Li W.Probabilistic transmission system planning[M].Piscataway,N.J.:Wiley-IEEE Press,2011.
[6]中华人民共和国电力行业标准,中国电力企业联合会,国家能源局.DL/T5729-2016配电网规划设计技术导则[S].北京:中国电力出版社,2016.
[7]初壮,乔福泉.考虑风电与负荷时序性的分布式风电源选址定容[J].电力系统及其自动化学报,2017,29(10):85-90.Chu Zhuang,Qiao Fuqian.Locating and sizing of distributed wind generation considering wind generation and the timing characteristics of load[J].Proceedings of the CSU-EPSA,2017,29(10):85-90(in Chinese).
[8]李振坤,岳美,胡荣,等.计及分布式电源与可平移负荷的变电站优化规划[J].中国电机工程学报,2016,36(18):4883-4893.Li Zhenkun,Yue Mei,Hu Rong,et al.Optimal planning of substation considering distributed generation and shiftable loads[J].Proceedings of the CSEE,2016,36(18):4883-4893(in Chinese).
[9]葛少云,王世举,路志英,等.基于分布式电源置信容量评估的变电站规划方法[J].电力系统自动化,2015,39(19):61-67.Ge Shaoyun,Wang Shiju,Lu Zhiying,et al.Substation optimization planning method based on capacity credit evaluation of distributed generator[J].Automation of Electric Power Systems,2015,39(19):61-67(in Chinese).
[10]刘浩军.考虑负荷特性的有源配电网变电站优化规划方法[J].电力系统及其自动化学报,2015(S1):126-131.Liu Haojun.Active distribution network substation optimization planning method considered load characteristics[J].Proceedings of the CSU-EPSA,2015(S1):126-131(in Chinese).
[11]杨毅,韦钢,周冰,等.含分布式电源的配电网模糊优化规划[J].电力系统自动化,2010,34(13):19-23.Yang Yi,Wei Gang,Zhou Bing,et al.Optimized fuzzy planning of the distribution network including distributed generation[J].Automation of Electric Power Systems,2010,34(13):19-23(in Chinese).
[12]程浩忠.电力系统规划:第2版[M].北京:中国电力出版社,2014.
[13]刘译聪,刘文霞,刘宗歧,等.广义电源高压配网替代容量的评估方法[J].现代电力,2018,35(5):79-87.Liu Yicong,Liu Wenxia,Liu Zongqi,et al.Evaluation method on capacity credit of generalized power source in high voltage distribution network[J].Modern Electric Power,2018,35(5):79-87(in Chinese).
[14]傅旭,肖汉,姚力,等.基于随机生产模拟的间歇性电源可信容量计算[J].智慧电力,2017,45(8):82-89.Fu Xu,Xiao Han,Yao Li,et al.Credit capacity calculation of intermittent power based on Stocha[J].Smart Power,2017,45(8):82-89(in Chinese).
[15]周辛南,柯德平,孙元章.基于配电网静态电压质量机会性约束的可再生能源分布式发电容量规划[J].电力自动化设备,2015,35(9):143-149.Zhou Xinnan,Ke Deping,Sun Yuanzhang.DG planning based on chance constraint of distribution network static voltage quality for renewable energies[J].Electric Power Automation Equipment,2015,35(9):143-149(in Chinese).
[16]罗奕,汪隆君,王钢.计及分布式电源出力相关性的微电网发电系统可靠性评估[J].电力系统自动化,2014,38(12):34-38.Luo Yi,Wang Longjun,Wang Gang.Reliability assessment of microgrid generation system considering output correlation of distributed generators[J].Automation of Electric Power Systems,2014,38(12):34-38(in Chinese).
[17]陈碧云,闭晚霞,李欣桐,等.考虑风-光-荷联合时序场景的分布式电源接入容量规划策略[J].电网技术,2018,42(3):755-761.Chen Biyun,Bi Wanxia,Li Xintong,et al.Capacity planning strategies for distributed generation considering wind photovoltaic load joint time sequential scenarios[J].Power System Technology,2018,42(3):755-761(in Chinese).
[18]李翔,顾洁.运用聚类算法预测地区电网典型日负荷曲线[J].电力与能源,2013,34(1):47-50.Li Xiang,Gu Jie.Using the clustering algorithm forecast in the power grid typical daily load curve[J].Power&Energy,2013,34(1):47-50(in Chinese).
[19]韦婷婷,王主丁,寿挺,等.基于DG并网运行的中压配网可靠性评估实用方法[J].电网技术,2016,40(10):3006-3012.Wei Tingting,Wang Zhuding,Shou Ting,et al.A practical reliability assessment method of distribution systems with grid connected DGs[J].Power System Technology,2016,40(10):3006-3012(in Chinese).
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