计及水流补偿风险的梯级水电发电权投标决策模型
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摘要
如何在天然来水不确定性引发的水流补偿风险背景下进行投标决策,是梯级水电参与发电权交易必须要考虑的问题。为此,提出了计及水流补偿风险的梯级水电发电权投标决策模型。在明晰水流补偿风险对梯级水电投标决策影响的基础上,基于梯级电站间彼此互动的复杂系统特性,利用元胞自动机为上、下游水电站联合而成的梯级共同体建模;根据是否具有水流补偿功能,将共同体内的上、下游电站分别视为龙头元胞、基础元胞,将补偿水流量、发电权申报量、价格作为各相关元胞的状态,并基于风险管控思想和水力发电等原理,分别建立龙头元胞和基础元胞的状态及状态转换决策模型,进而实现水流补偿风险与电站出力的关联;以最大化梯级共同体的申报量为目标,上、下游元胞按照邻域关系互动,利用水力发电等原理,建立梯级共同体参与发电权交易的协同投标决策模型。
Approaches to make bidding decisions under water flow compensation risks caused by the uncertainty of natural inflow represent a necessary problem that should be considered for the cascade hydropower taking part in PGRT( Power Generation Rights Trading). Motivated by this,the bidding decision model of cascade hydropower taking part in PGRT considering compensation risks is proposed. The impacts on PGRT caused by compensation risks are analyzed. Then,the model of CC( Cascade Community) considering complex system characteristics of interaction between cascade hydropower stations is illustrated based on cellular automata theory. According to the water flow compensation function,the upstream and downstream stations in CC are divided into the leading and basic cells.The quantity of compensating water,quantity of power generation rights bidding and price are selected as the attributes of the cells. Then,the state models and state transition models of leading and basic cells are constructed based on the principles of risk management and hydropower generation theory,respectively. Consequently,the relationship between the compensation risks and the output of CC is established. To maximize the bid quantity of CC,the upstream and downstream cells interact with each other according to neighborhood relationships,and the bidding decision model of CC is proposed based on the principles of hydropower generation and other factors.
Approaches to make bidding decisions under water flow compensation risks caused by the uncertainty of natural inflow represent a necessary problem that should be considered for the cascade hydropower taking part in PGRT( Power Generation Rights Trading). Motivated by this,the bidding decision model of cascade hydropower taking part in PGRT considering compensation risks is proposed. The impacts on PGRT caused by compensation risks are analyzed. Then,the model of CC( Cascade Community) considering complex system characteristics of interaction between cascade hydropower stations is illustrated based on cellular automata theory. According to the water flow compensation function,the upstream and downstream stations in CC are divided into the leading and basic cells.The quantity of compensating water,quantity of power generation rights bidding and price are selected as the attributes of the cells. Then,the state models and state transition models of leading and basic cells are constructed based on the principles of risk management and hydropower generation theory,respectively. Consequently,the relationship between the compensation risks and the output of CC is established. To maximize the bid quantity of CC,the upstream and downstream cells interact with each other according to neighborhood relationships,and the bidding decision model of CC is proposed based on the principles of hydropower generation and other factors.
引文
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[19]丁明,楚明娟,毕锐,等.基于序贯蒙特卡洛随机生产模拟的风电接纳能力评价方法及应用[J].电力自动化设备,2016,36(9):67-73.DING Ming,CHU Mingjuan,BI Rui,et al.Wind power accommodation capability evaluation based on sequential Monte Carlo probabilistic production simulation and its application[J].Electric Power Automation Equipment,2016,36(9):67-73.
[20]王小平,曹立明.遗传算法:理论、应用与软件实现[M].西安:西安交通大学出版社,2002:18-29.
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[22]袁旭峰,韩士博,熊炜,等.计及梯级水电站群的水火电节能调度模型[J].电网技术,2014,38(3):616-621.YUAN Xufeng,HAN Shibo,XIONG Wei,et al.Energy-saving generation scheduling strategy of hydropower and thermal power plants considering cascaded hydropower stations[J].Power System Technology,2014,38(3):616-621.
[23]张维,范玉宏.华中电力市场双边交易模拟分析[J].电力系统自动化,2008,32(11):97-102.ZHANG Wei,FAN Yuhong.Analysis on bilateral transaction simulation of central China electricity market[J].Automation of Electric Power Systems,2008,32(11):97-102.
[2]张显,耿建,庞博,等.发电权交易在中国节能减排中的应用及分析[J].电力系统自动化,2014,38(17):87-90.ZHANG Xian,GENG Jian,PANG Bo,et al.Application and analysis of generation right trade in energy-saving and emission reduction in China[J].Automation of Electric Power Systems,2014,38(17):87-90.
[3]王雁凌,张粒子,杨以涵.基于水火置换的发电权调节市场[J].中国电机工程学报,2006,26(5):131-136.WANG Yanling,ZHANG Lizi,YANG Yihan.Adjusting market of generation rights based on hydro-thermal exchange[J].Proceedings of the CSEE,2006,26(5):131-136.
[4]于琪,张晶,王宣元,等.区域发电权交易网省协调优化模式研究[J].电力自动化设备,2013,33(3):90-95.YU Qi,ZHANG Jing,WANG Xuanyuan,et al.Coordinated optimization between regional and provincial grids for regional generation trade[J].Electric Power Automation Equipment,2013,33(3):90-95.
[5]傅鸿浩,蔡国田,赵黛青.计及环境成本的跨省输电发电权交易及敏感性分析[J].电力自动化设备,2014,34(9):101-111.FU Honghao,CAI Guotian,ZHAO Daiqing.Generation right trade of trans-province power transmission considering environmental cost and sentivity analysis[J].Electric Power Automation Equipment,2014,34(9):101-111.
[6]邹斌,赵岩,李晓刚,等.跨省跨区清洁能源消纳的市场机制研究[J].电网技术,2016,40(2):595-601.ZOU Bin,ZHAO Yan,LI Xiaogang,et al.Market mechanism research on trans-provincial and trans-regional clean energy consumption and compensation[J].Power System Technology,2016,40(2):595-601.
[7]XIAO Jian,WEN Fushuan,HUAN Jiansheng.Congestion dispatch in a hybrid generation-rights market[J].European Transactions on Electrical Power,2011,21(1):1046-1053.
[8]韩冰,张粒子,舒隽.梯级水电站代理竞价模型及均衡求解[J].中国电机工程学报,2008,28(22):94-99.HAN Bing,ZHANG Lizi,SHU Jun.Bidding model of cascaded hydropower stations and equilibrium solving under agency mechanism[J].Proceedings of the CSEE,2008,28(22):94-99.
[9]舒隽,韩冰,张粒子.市场环境下梯级水电资源有效配置的代理机制[J].电力系统自动化,2010,34(7):26-30.SHU Jun,HAN Bing,ZHANG Lizi.An agency mechanism on ensuring efficient deployment of cascade hydropower resources in an electricity market environment[J].Automation of Electric Power Systems,2010,34(7):26-30.
[10]钟平安,张梦然,蔡杰,等.基于决策树的梯级水电站泄流补偿调度风险分析[J].电力系统自动化,2012,36(20):63-67.ZHONG Pingan,ZHANG Mengran,CAI Jie,et al.Risk analysis on flow discharge compensating operation for cscade hydroelectric stations based on dicision tree[J].Automation of Electric Power Systems,2012,36(20):63-67.
[11]WEI Y,SHANG Y,FAN Y,et al.The cellular automaton model of investment behavior in the stock market[J].Physica A:Statistical Mechanics and its Applications,2003,325(3-4):501-516.
[12]姜爱克,李雪岩,李雪梅,等.基于策略演化的股票市场元胞自动机模型[J].北京交通大学学报,2013,37(3):154-160.JIANG Aike,LI Xueyan,LI Xuemei,et al.Cellular automata of stock market based on strategy evolution[J].Journal of Beijing Jiaotong University,2013,37(3):154-160.
[13]栾笑天,吴桐水,寇勇刚.基于CA方法的航空物流市场演化模型设计[J].复杂系统与复杂性科学,2013,10(4):31-40.LUAN Xiaotian,WU Tongshui,KOU Yonggang.Design the evolution model of aviation logistics market with cellular automata[J].Complex Systems and Complexity Science,2013,10(4):31-40.
[14]周湶,李健,孙才新,等.基于粗糙集和元胞自动机的配电网空间负荷预测[J].中国电机工程学报,2008,28(25):68-73.ZHOU Quan,LI Jian,SUN Caixin,et al.Spatial load forecasting for distribution network based on rough sets and cellular automata[J].Proceedings of the CSEE,2008,28(25):68-73.
[15]宋玉蓉,蒋国平.基于一维元胞自动机的复杂网络恶意软件传播研究[J].物理学报,2009,58(9):5911-5917.SONG Yurong,JIANG Guoping.Research of malware propagation in complex networks based on 1-D cellular automata[J].Acta Physica Sinica,2009,58(9):5911-5917.
[16]魏雷,林鑫,王猛,等.基于Mesh TV界面重构算法的二元合金自由枝晶生长元胞自动机模型[J].物理学报,2012,61(9):497-506.WEI Lei,LIN Xin,WANG Meng,et al.Cellular automaton model with Mesh TV interface reconstruction technique for alloy dendrite growth[J].Acta Physica Sinica,2012,61(9):497-506.
[17]王砚帛,谭永东,文菓,等.基于Fisher判别和元胞自动机模型的微电网格局计算方法[J].电网技术,2012,36(11):12-17.WANG Yanbo,TAN Yongdong,WEN Guo,et al.An approach to calculate micro-grid's configuration based on Fisher discriminant and cellular automata model[J].Power System Technology,2012,36(11):12-17.
[18]刘自发,庞铖铖,王泽黎,等.基于云理论和元胞自动机理论的城市配电网空间负荷预测[J].中国电机工程学报,2013,33(10):98-105.LIU Zifa,PANG Chengcheng,WANG Zeli,et al.Spatial load forecast for distribution network based on cloud theory and cellular automata[J].Proceedings of the CSEE,2013,33(10):98-105.
[19]丁明,楚明娟,毕锐,等.基于序贯蒙特卡洛随机生产模拟的风电接纳能力评价方法及应用[J].电力自动化设备,2016,36(9):67-73.DING Ming,CHU Mingjuan,BI Rui,et al.Wind power accommodation capability evaluation based on sequential Monte Carlo probabilistic production simulation and its application[J].Electric Power Automation Equipment,2016,36(9):67-73.
[20]王小平,曹立明.遗传算法:理论、应用与软件实现[M].西安:西安交通大学出版社,2002:18-29.
[21]张剑,何怡刚.基于无向图所有生成树的网络重构遗传算[J].电力自动化设备,2017,37(5):136-141.ZHANG Jian,HE Yigang.Genetic algorithm based on all spanning trees of undirected graph for distribution network reconfiguration[J].Electric Power Automation Equipment,2017,37(5):136-141.
[22]袁旭峰,韩士博,熊炜,等.计及梯级水电站群的水火电节能调度模型[J].电网技术,2014,38(3):616-621.YUAN Xufeng,HAN Shibo,XIONG Wei,et al.Energy-saving generation scheduling strategy of hydropower and thermal power plants considering cascaded hydropower stations[J].Power System Technology,2014,38(3):616-621.
[23]张维,范玉宏.华中电力市场双边交易模拟分析[J].电力系统自动化,2008,32(11):97-102.ZHANG Wei,FAN Yuhong.Analysis on bilateral transaction simulation of central China electricity market[J].Automation of Electric Power Systems,2008,32(11):97-102.