Research On Life Style Cost Management Of 500KV Substation In Inner Mongolia

With the rapid development of China's national economy, the proportion of electric power in energy consumption structure gets greater year by year. Driven by the tremendous power demand, the pace of power construction around China happen to coincide speeding up, the amount of electricity investment is also correspondingly accelerated, because the substation investment as well as the operation and maintenance costs play an important role in the whole power system, so the study of Life Cycle Cost of the substation has important economic value.This paper combined with the characteristics of substation costs in each stage, set up the substation Life Cycle Cost (LCC) model, using Life Cycle Cost theory, ulteriorly calculated substation Life Cycle Cost (LCC) using fish-swarm neural network algorithm and blind number theory, the main research work are as follows:Firstly, this paper analyzed the content and characteristics of substation Life Cycle Cost, established a estimate model of the substation Life Cycle Cost, which consider not only the substation one-time investment, but also the operation and maintenance expenses as well as the cost of power supply interruption and disposal cost. So this model is more tally with the actual situation, and has more important practical economic meaning.Secondly, this paper analyzed the impact of station on the substation supply region, which including the impact on the environment, economy and society. Consider the macroeconomic costs; this paper compared the ecological niche of station supply region before and after the substation's construction in order to control the macroeconomic costs.Thirdly, this paper estimated the substation Life Cycle Cost using the fish-swarm neural network algorithm.The estimation of the Life Cycle Cost has some shortcomings as follows:it involves a long time, has multiple indexes and complicated computed process, at the same time it is vulnerable to the impact of human factors. Neural network can estimate the cost rapidly through selecting several representative indexes. Nevertheless, neural network has its own shortcomings, such as slowed Training speed, the problem of low efficiency and local optimum and so on, in order to solve these problems, this paper used the fish-swarm algorithm optimize the neural network model to make it more reasonable.Fourthly, this paper estimated the substation Life Cycle Cost using blind number theory.There are a variety of uncertain information in the Substation lifecycle, which possesses different characteristics and nature as well as random, fuzzy, and interval, so it is clearly not accurate to adopt a single uncertain method to analyze the substation Life Cycle Cost. Nevertheless, using the blind number theory to describe and deal with such uncertain information can calculate a more real cost while retaining the effective information to the utmost extent.Fifthly, the substation Life Cycle Cost has different risks at different stage, and each risk has various influenced degree. This paper classified the risks according to the analysis of these risks, calculated the estimate of these risks, and proposed some recommendations to control these risks that occurred in the process of the station operation.Sixthly, because the various parameters that affected the substation Life Cycle Cost is not fixed, so this paper expounded the meaning of the LCC sensitivity analysis and the implication of LCC sensitivity analysis in the process of substation construction. The values of sensitivity function and parameters were used together to determine the sensitivity of LCC to each parameter.