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论文摘要

市场环境下梯级水电站间发电补偿效益研究

Research on Power Generation Compensation Benefits of Cascade Hydropower Stations in Power Market

作者:王金龙(四川大学水力学与山区河流开发保护国家重点实验室);黄炜斌(四川大学水力学与山区河流开发保护国家重点实验室);马光文(四川大学水力学与山区河流开发保护国家重点实验室);郭乐(中国长江三峡集团公司)

Author:Wang Jin-long();HUANG Wei-bin(State Key Lab. of Hydraulics and Mountain River Eng., Sichuan Univ.);();()

收稿日期:2015-03-24          年卷(期)页码:2016,48(3):79-86

期刊名称:工程科学与技术

Journal Name:Advanced Engineering Sciences

关键字:联合调度;核定电量;补偿效益分摊;改进单亲遗传算法;梯级水电

Key words:united operation; electric energy benchmark; compensation benefits allocation; improved partheno genetic; cascade hydropower stations

基金项目:2013CB036406-4

中文摘要

为解决现有梯级水电发电补偿效益核定办法及分摊方法存在的不足,提出了基于“核定电量”概念的补偿效益计算法,建立了能够同时兼顾各电站主观偏好且保持群体一致性的效益协调分摊模型。新计算法考虑到了市场环境下各电站的分期电价差异和电网对其增发电量的吸收约束,使得基于梯级实际联合运行结果和核定电量计算结果得到的补偿效益更贴近实际。新模型依据各方协商确定的分摊原则,先以单站分摊比例最大为目标求得个体偏好下的分摊原则权重向量,然后按照群体一致性原理求解各分摊原则的群体权重,最后以距离不同分摊原则的分摊结果最近为目标计算各电站的分摊比例,整个过程采用改进单亲遗传算法求解相关优化目标,参数少、操作简单、易于控制。实例计算结果公平、合理,易于各方接受,可为不同主体的梯级水电联合调度增发效益补偿提供参考。

英文摘要

In order to solve the inadequacies of existing calculation and allocation methods of the power generation compensation benefits (PGCB) which come from united operation of cascade reservoirs, a new concept, electric energy benchmark of hydro plant, was proposed and used to calculate PGCB, and also a new model for allocating PGCB among cascade hydro plants was developed, which can balance the subjective preference of each plant and the group consistency of all plants. The proposed computing method takes into account TOU power price differences among different plants and load rate constraint from power grid for the electric energy output increasing of every plant, which makes the method get closer to the real value of PGCB. According to the benefits-sharing principles selected by involved parties, the proposed model firstly gets the individual preference weight vector of every plant for the principles by solving an optimal model whose goal is maximum single plant apportionment ratio; secondly, reach a consensus on the weight vector through maximizing group consistency; finally, the actual benefits –sharing proportion of every plant is fixed by solving another optimal model whose goal is minimizing the distance between the final values and the results from all the different principles. Moreover, an improved partheno genetic algorithm, whose genetic operation is simple and more efficient, was presented and adopted to solve all the relevant optimal models. A case study shows that the proposed computing method and benefits-sharing model work well, and the results are reasonable and can be accepted more easily.

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