Application Of Electric Equipment Investment Decision-making Based On LCC Theory

Electricity is a strategic energy concerning the lifeline of national economic and social development. In recent years, government continues to increase investment in the power grid, construction of power grids is in the high-speed developing stage. Investment in electrical equipment is an important part of the fixed assets investment of the enterprises in power grid, the success or failure of the investment decision-making relates to the cost of power enterprises, the utilization of funds and even competitiveness and viability in the market-oriented reforms. Currently, a common phenomenon which taking the short-term costs seriously and neglecting the long-term costs is existed in electrical equipment procurement process, therefore in the investment decision-making process of the power equipment, it is a topic worthy of further study on how to proceed from the overall objectives of system, consider the whole process containing power equipment procurement, operation, maintenance, failure and discard, pursuit the minimum equipment life cycle cost and achieve system optimization on the premise of security and efficiency.The full life cycle cost (LCC) theory is introduced into the electrical equipment investment decisions in this paper aimed at the characteristics of traditional power equipment procurement process which emphasis on one-time investment and underestimate or even ignore the late investment on the equipment. Life cycle cost of the power equipment will be refined and divided into five parts, the initial investment costs, the operation costs, the maintenance costs, the failure costs and the discard costs.The concrete work as follows:1. The concept and features of whole life cycle cost is expounded, life cycle cost breakdown structure (CBS) of power equipment is constructed, the estimating relationship between various components of the cost is built, the estimating model of full life cycle cost of the electrical equipment is determined combining the concept of the time value of capital.2. Interval number theory is used to deal with uncertainty in the power equipment parameters. The concept and calculation of interval number theory is introduced, the full life cycle cost model is established based on interval analysis method, it is applied to a specific instance to get a conclusion and the optimal program is selected.3. Blind number theory is used to deal with various uncertain information existed in power equipment, the full life cycle cost estimation model which is based on blind number is established, the full life cycle cost estimates based on blind number theory method is illustrated practical and rational through example of switchgear AIS and GIS selection.4. The neural network is introduced to estimate the full life cycle cost of power equipment which makes the complex calculation simpler and the calculation with the subjective factors more objective, and the most economical solution is selected through neural network analysis of full life-cycle on four prepared plan for 500kV substation construction.5. General net present value method is used to estimate the life cycle cost of power transformer and switchgear equipment, the specific data of costs in the full life cycle is displayed in the form of a table, the most economical solution is choosed. Above four methods which are used to estimate the life cycle cost are compared and analyzed, their respective advantages and applicable scope are summed up.6. The platform building of life cycle cost estimation of power equipment is designed and completed and the Web publishing of full life cycle cost of power equipment is realized. The building of management platform of life cycle cost of power equipment in B/S model is proposed, customers only need to open a web page and log in browser to get related electrical equipment parameters which makes it convenient for customers to make decision when buying power equipment.Applying full life cycle cost theory to the power equipment investment decisions could improve efficiency procurement, it has important economic value by unifying the goal of device multistage and achieving the optimization of overall system.