电力市场辅助服务几个问题的研究
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摘要
近年来许多国家都在进行电力市场的改革,电力市场成为当今研究的一个热点。辅助服务是电力市场中必不可少的重要组成部分,是电力系统安全、稳定、高效运行的重要保证。本文主要针对电力市场中辅助服务问题中的无功服务和网损分摊等问题进行了研究。
    无功服务是电力市场中不可或缺的一种服务。本文主要研究了无功服务中的无功定价和模糊无功优化问题。由于无功服务的特殊性,无功的定价问题比有功定价问题显得相对复杂。在分析总结了现有无功定价方法的基础上,提出了基于电流迭加法的无功定价新方法。该方法在某一的潮流运行点下,对电网进行等效,利用迭加原理,分别计算此时各电源对负荷的电流贡献,然后再求得其对负荷的功率贡献,最后依据成本分摊进行电价计算。该方法适用于存在环流的网络,有效地解决了发电机进相运行时生产的成本回收问题,并将负荷有功、无功电价计算有效地统一起来;它计算简单,实用性强。文中对此方法进行了详细的理论证明,完成算法程序的编写,最后以IEEE-14和IEEE-30 节点系统为例进行了仿真计算,验证了该方法的合理性。
    利用电流迭加法进行了网损分摊的研究。该方法根据各电源对支路的使用程度计算各电源对各支路应承担的损耗,从而计算系统网损在电源中的分摊。根据电源对负荷的功率贡献因子计算电源和负荷分别承担网损及它们按比例承担时的系统网损分摊。该方法不仅能计算有功网损的分摊和而且能同时计算无功网损的分摊,计算简单、适应性强、符合电力市场中的实际情况。文中对此方法从理论上给予了证明,并进行了仿真计算。
    针对负荷的不确定性,建立了电力市场中的模糊无功优化模型。该模型通过将模糊数引入到电力系统无功优化中,解决了负荷预测不确定情况下的优化问题,从而使电力市场中的无功优化更加符合实际,更加可信。采用模糊理论与遗传算法相结合的方法,有效地解决了非线性模糊优化问题的求解,得到了较好的效果。编写了求解算法程序,并针对一个实际地区的系统进行了仿真计算,得到了在不同负荷置信度水平下的优化结果。
In recent years, the deregulation of power system is carried out in some countries. The ancillary service is an important part of the power market. It is vital to the safety, stability and efficiency of power system. This paper discusses the reactive power service and the allocation of power losses.
     Reactive power service is the indispensable service of power market. Pricing of reactive power and the fuzzy reactive power optimization are studied in this paper. Because of its specialties, the pricing of reactive power is more complex. This paper proposes a novel method for reactive power pricing. The superposition theorem is used to calculate the contributions of individual generators to loads in a given status and the active and reactive power price of loads is determined by cost apportioning. It is applicable to the network in which the circumfluence exists. Pricing of active and reactive power is integrated efficiently. The problem that how to recover the cost of the generators which operate in the under excitation condition is resolved successfully. The simplicity and practicability of the method is evidence. Finally with the IEEE-14 and IEEE-30 bus systems as the examples, the simulation computing is carried out. The validity and feasibility of the method is demonstrated by the results.
    In this paper, the method of current superposition is used to allocate the power losses. The apportionment of each power source is calculated on the basis of its actual use of each branch. The losses allocation between the power sources and loads in certain proportion is calculated on the basis of the factor of contributions of individual generators to loads. Not only can the allocation of the active power losses but also that of the reactive power losses be calculated at the same time. The simplicity and good adapbility of the method is obvious. The rationality of the method is proved by the examples.
    The model of the fuzzy reactive power optimization is established in order to consider the uncertainty of the loads. The fuzzy set is introduced into the reactive power optimization, so the optimization becomes more reasonable and practical. The fuzzy theory and the genetic algorithms are combined to solve the fuzzy nonlinear optimization problem. A real system is used as an example to test the method.
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