摘要
随着电力工业的迅速发展,电力设备的投资不断增加。实现对电力设备成本的有效控制,关系着电力工业的健康发展。然而,目前在对电力设备成本模型的研究中,只考虑了设备的初期投入成本,忽视了设备的运行维护成本,而这一部分在整个设备投资中占有非常重要的份额,因此,对电力设备的成本模型进行研究具有重要的经济价值。
全寿命周期成本(Life Cycle Cost,LCC)分析是从项目的长期经济效益出发,全面考虑设备或系统的购置、安装、运行、维修、更新,直至报废的全过程,使LCC最小的一种理论和方法。LCC是一种系统分析方法,追求的是设备一生所耗资源最节省。
但是在LCC的分析中,通常只考虑了如何降低电力设备的成本,而忽视了随之产生的电力设备效能的变化,然而,电力设备效能的实现是保障电力系统安全稳定运行的基础。因此,需要综合考虑电力设备的费用和效能,以评估LCC模型的可行性。
传统的LCC决策和费用-效能评估方法的应用前提,是已知大量的历史数据;而在实际应用中,很多数据是难以获取的。灰色系统理论可以在信息不充分的条件下,取得尽可能准确的分析结果。因此,本文提出将灰色系统理论运用到电力设备LCC的分析和费用-效能评估中。主要研究工作如下:
①探讨了电力设备LCC组成部分的内容和特点,比较了几种常用的LCC估算方法,指出这几种估算方法在数据较少的情况下,都不能对LCC进行较准确的估算。
②研究了电力设备LCC的定量估算模型。在将电力设备LCC分为一次性投资费用和运行维护费用的基础上,将瞬时值计算引入到一次性投资费用的分析中,并提出将基于灰关联加权组合的预测理论及最大关联度原则引入到运行维护费用的分析中,综合分析这两部分,估算最小LCC。
③分析了电力设备费用-效能评估的意义。针对电力设备费用-效能评估指标具有模糊性和灰色性的特点,提出基于灰色模糊的费用-效能评估方法。通过三角隶属度函数描述评估因素与评估等级间的模糊关系,并引入点灰度描述模糊关系的不可信程度。在此基础上进行灰色模糊综合评估,得到更贴近实际的评估结果。
④算例验证了论文所提方法的有效性。
Along with the quick development of electric power industry, electric power equipment's investment increases unceasingly. Carry out the active control of electric power equipment cost, relates to electric power industry's healthy development. However, in the research of electric power equipment’s cost model currently, the initial period invested cost of equipment has been considered only, but the running and sustaining cost of equipment has been neglected, although this part holds a very important share in the entire equipment investment, therefore, the research on electric power equipment’s cost model has an important economic value.
Life Cycle Cost(LCC) analysis is an idea if considering item’s long-term economy benefit, which makes LCC minimum if all things considered such as purchasing, fixing, running, sustaining, updating and discarding of equipment or system. The LCC is a kind of system analysis method, which tries to make the long cost come to its minimum point.
But in LCC analysis, the way how to reduce electric power equipment cost has been considered, but the changes of electric power equipment effectiveness which produce along with it have been neglected, however, electric power equipment effectiveness's realization is the foundation that guarantees safe and steady operation of electric power system. So the cost and the effectiveness of electric power equipment are need to be considered comprehensively, and they can use to assess the feasibility of LCC model.
The applied premise of the traditional methods of LCC decision and cost-effectiveness assessment is that a huge amount of historical data has been already known, but it’s difficult to receive so much data in practical application. Under the premise that the information is insufficient, the grey system theory can get accurate analysis result as far as possible. So the paper proposes applying grey system theory to carry on the analyzation of LCC and cost-effectiveness assessment for electric power equipment. The main research works in this paper are as follows:
①The paper discusses the content and the characteristic of every part of electric power equipment LCC, compares among several LCC estimation methods which are used commonly, points out that these estimation methods cannot estimate to LCC accurately in the situations that data is little.
②The paper studies the quantitative estimation model of electric power equipment’s LCC. On the basis that the electric power equipment’s LCC is set off one-off investment cost and running and sustaining cost,the paper introduces the instantaneous value calculation into the analyzation of one-off investment cost, and introduces the forecasting theory based on grey relational weighing combination and the most relational degree principle into the analyzation of running and sustaining cost, estimates the minimum LCC by analyzing the two parts comprehensively.
③The paper analyzes the meaning of electric power equipment’s cost-effectiveness assessment. Aiming at the feature that the factors of electric power equipment’s cost-effectiveness assessment are grey and fuzzy,the paper proposes a cost-effectiveness’s assessment method based on grey fuzzy. The triangular membership function is built up to describe the fuzzy relation between assessment factors and assessment grades, the unlikelihood extent of fuzzy relation is described by leading in grey scale value of pixel. On this basis the grey fuzzy comprehensive assessment is conducted, and the assessment result more near to the practice is achieved.
④Validate the validity of method proposed in this paper by cases.
引文
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