Life-cycle cost model and evaluation system for power grid assets based on fuzzy membership degree

0 Introduction

In recent years, electric power companies have intensified life-cycle cost (LCC) research to improve asset management and operational efficiency and respond to governmental supervision of grid transmission costs [1-2].In the power industry, LCC analysis can be applied to the procurement, modernization, and overhaul of power plant equipment, the establishment of a standard operating cost database, the development of equipment scrapping strategy, and the industry-level assessment of overall cost management and asset management [3-16].

Further, LCC can be used to effectively improve industry management practices and facilitate lean asset management.Researchers have explored different approaches to power substation modernization, equipment service-life assessment, procurement management, operation and maintenance management, and project closure, with a focus on the gradual improvement of electrical power industry practices from the perspective of basic theory development,decision-making support, and standard practice evaluation[17-26].However, a shortage of easy-to-operate LCC models and methods exists that can be readily used by the power industry, particularly for multiple difficult-toquantify assets that must be properly allocated.

In China’s electric power industry, implementation of LCC practices has been relatively slow, and there is no management or work standard for different operating scenarios [27-30].Establishment of standard practices and evaluation systems for asset service-life management,and research on the application of LCC for equipment procurement decision-making, equipment modernization and overhaul decision-making, establishment of a standard cost database, development of equipment scrapping strategy, overall cost management, and asset management benchmarking can facilitate effective asset management and promote lean asset management in the power industry.

This paper proposes an LCC model for electric power equipment management to assist power industry enterprises in managing assets and equipment.To address the problem of multiple shared equipment units and assets in modernization and overhaul projects, we use fuzzy membership functions to construct the LCC model and the evaluation system.The proposed model was successfully applied to the project decision-making of a power plant in the China Southern Power Grid (Guangzhou area),effectively improving the operation and efficiency of the power equipment.

1 LCC management of power equipment

LCC assessment of power equipment involves estimation of expected costs—including the initial capital, modernization, troubleshooting, operation and maintenance—and disposal costs within the useful life of the asset.The LCC management of power equipment requires constructing a life-cycle inventory, which involves the following steps:

(1) Clarifying asset boundaries and organizing fixed asset records

In the electric power industry, LCC management encompasses the physical assets of a power plant including the generation, transmission, transformation, primary and secondary distribution, measurement, and communication systems owned by the enterprise.Defining asset boundaries is a critical aspect of life-cycle management; for an ultrahigh-voltage (UHV) power plant in the Guangzhou branch of the China Southern Power Grid, defining system boundaries, allocating asset portfolios, formulating classification standards, and bridging data gaps must be considered.

(2) Establishing goals for each stage of the asset life-cycle

Assets are categorized based on their function; short-,medium-, and long-term goals are determined according to their importance, with priority given to those involving a high proportion of the original fixed asset value, such that the full scope of the asset life-cycle is addressed.

2 LCC model for power equipment

The allocation coefficient method is used to allocate the production project cost of power equipment to the LCC.The operational and management cost dimensions of the asset and production project cost dimensions are linked to form the LCC database of production project assets.The LCC of the allocated power equipment is expressed as

where CLCCi is the LCC of the ith allocated power equipment unit; ai is the asset allocation coefficient assigned to the ith power equipment unit; Cj is the sum of the asset production project costs including the cost of modernization, overhaul,operation, and maintenance.

The allocation coefficient ai is calculated using one of two methods depending on the type of project: (1) in operation and maintenance projects, the allocation coefficient can be computed directly; (2) in modernization and overhaul projects, which involve non-computable indexes, the fuzzy membership function is used to calculate the allocation coefficient.

(1) Operation and maintenance projects

In the project approval stage, a list of substations/converter stations and different types of equipment associated with the project must be prepared.The associated asset list should be reviewed in the project closure stage, at which time the project closure cost should be allocated to the associated assets based on the proportion of the original value of the fixed assets using Eq.(2):

where C1j is the original fixed asset value of the jth project,and C2j is the original fixed asset value of the associated assets of the jth project.A flowchart of the allocation process is shown in Fig.1.

Fig.1 LCC allocation flowchart for operation and maintenance projects

(2) Modernization and overhaul projects

In the project approval stage, a list of assets associated with the project must be prepared.In the project closing stage, the list of associated equipment assets should be reviewed, and the project settlement amount should be allocated to the associated assets according to specific allocation coefficients.A flowchart of the allocation process is shown in Fig.2.

Fig.2 LLC allocation flowchart for modernization and overhaul projects

In this case, the asset allocation coefficient ai is not computed; it must be determined according to the type of production project, classified as asset value, frequency of occurrence, or time-related project type using the fuzzy evaluation method.A notable feature of the fuzzy evaluation method is that the evaluation result is not a simple score or comment; rather, it is a fuzzy membership vector.Fuzzy vectors are frequently used to score non-numeric indexes.Unlike other methods, the fuzzy set method does not require strict comparability of the evaluated indexes, and thus, allows for simpler and more reasonable use of expert experience and facilitates the use of non-numeric indexes.

A comprehensive fuzzy evaluation method requires the use of fuzzy vectors.In a single-factor fuzzy scoring evaluation, the computable indexes are transformed into fuzzy vectors used to score the non-numeric indexes.In this study, the decision set V ={v1 , v2 ,… , vm} is defined using five classification levels (m=5), and the comment domain is defined as high, moderately high, medium, moderately low, or low.For each index, the relationship between the index value and the comment domain is established as

The fuzzy scores of the non-numeric indexes are assigned directly by experts using a 100-point system derived empirically from statistical data; the five comment indexes are scored to obtain a fuzzy vector B～ki, which is then normalized.For a substation modernization project, experts from relevant departments of the power plant use the fuzzy evaluation method to score the allocation coefficient ai to obtain a fuzzy vector.

For the scoring result of an expert, the weighted fuzzy vector becomes the comprehensive evaluation result on the decision set V through the fuzzy set is where

and ◦,andare fuzzy operators; ◦ represents fuzzy matrix multiplication; represent (·,+), indicating that for a specific expert score, bj is obtained based on the weighted average of all expert scores such that

Each allocation coefficient corresponds to one comprehensive evaluation vector

The fuzzy evaluation result is a fuzzy vector.The maximum membership degree can be used to assign an evaluation comment for each allocation coefficient; however,such evaluation is not conducive to intuitive comparison;thus, it is transformed into a single value, and a single score is assigned to each allocation coefficient.Score values{c1,c2,c3,c4,c5}are assigned from high to low for each comment,such that if a100-point system isused,the score values are {90, 70, 50, 30, 10}; the evaluation result for each allocation coefficient can be converted into a single value by

The last calculated ci is the percentage allocation coefficient ai, which must be normalized by

3 LCC evaluation system for power equipment

Based on the data in the asset LCC database for the production project, an evaluation system is established to perform a multi-dimensional LCC analysis of the project, providing a decision support mechanism for the procurement, modernization, and overhaul of the power plant equipment.

The LCC evaluation index system consists of four categories: cost rate, standard cost rate for similar assets,cost ratio, and standard cost curve for similar assets; each category can be further divided into subcategories based on the project type.

(1) Cost rate index

Given that an asset has been in operation for N years, the cost rate index for the Nth year of the asset is expressed as

where rc is the cost rate index; CLCC is the project LCC cost,and C1 is the initial investment cost of the power equipment.

(2) Standard cost rates for similar assets

Assets of the same type are selected as a sample and the standard cost rate index of the sample is calculated.When the sample size is small, an arithmetic mean can be used,such that

where rs is the standard cost rate and M is the sample quantity.When the number of samples is sufficiently large,data fitting can be used to obtain the standard cost rate curve for similar assets, as shown in Fig.3.

Fig.3 Standard cost rate curve for similar assets

(3) Standard cost ratio for similar assets

When a certain asset has been used for N years, the cost ratio of the asset in the Nth year is expressed as

where λ is the cost ratio index.

Comparable assets are selected as the sample, and the cumulative cost ratio of the sample is calculated.The cost ratio index for the same type of asset in year N is calculated;when the sample size is small, the arithmetic mean can be used to calculate the standard cost ratio for the same type of assets.

4 LCC application for power plant equipment

4.1 LCC-based decision-making for equipment procurement

Considering a UHV power plant in the China Southern Power Grid, we performed an LCC analysis of its assets and obtained the standard cost ratio curve for a specific type of equipment, as shown in Fig.4.

Fig.4 Standard cost ratio curve for specific type of assets

Fig.4 displays the production input evaluation index for this type of equipment.The production input coefficient can also be used to evaluate the production input for different suppliers, equipment models, and operation and maintenance units for similar types of assets.After selecting the cost ratio indexes for different suppliers, equipment models, and operation and maintenance units for similar assets, we calculate their respective production input coefficients using Eq.(11).

where β is the production input coefficient used to evaluate the production input.

In addition, the production input index of the asset supplier in Eq.(12) can be used to evaluate the quality of the supplier’s equipment.

where C0i is the original value of the ith asset, and η is the evaluation index of the supplier’s production input.In their procurement decision-making process, power plants often focus on the purchase cost of equipment and fail to comprehensively consider the service-life cost of the equipment in terms of its design, operation, maintenance,repair, and decommissioning costs.This practice has led to fierce pricing competition; manufacturers are inclined to reduce manufacturing costs, using inferior design, materials,or components, and neglecting to control the quality of the manufacturing process, ultimately resulting in low-quality products.Consequently, the probability of equipment failure increases, as do operation and maintenance costs,significantly impacting the safety and efficiency of power plant operation.The supplier’s production input evaluation index should be ranked and scored every year:a lower evaluation index indicates a higher score.Careful consideration should be given to the 10% of suppliers with the highest scores to determine the cause of their poor performance.Suppliers whose production input is significantly greater than that of similar-class suppliers should be blacklisted.

4.2 LCC-based decision-making in powerequipment modernization and overhaul projects

LCC-based assessment of a modernization and overhaul plan for a single equipment unit is performed under the premise of meeting safety and efficiency requirements,while also considering service life, monitoring requirements,and technical parameters.The LCC cost of different modernization and overhaul plans can be used as a reliable decision-making support mechanism.Investment decisions are based on the principle of lowest asset LCC.The annual LCC value is calculated separately for modernization and overhaul plans; the plan with the lowest annual value is selected.

If the design life of an asset was N1 years at the time it entered production, and it has been in operation for N2 years,and the current operation is maintained, it is expected to continue to operate for N3 years, where N 3 ≤ N1 - CN2.If the modernization plan is implemented, the asset is expected to continue to operate for N4 years, where N 4 ≥ N3.If the overhaul plan is implemented, the asset is expected to continue to operate for N5 years, where N 5 ≥ N3.Then,

where ALCC3 is the annual LCC value under the current operating plan; LCC3 is the LCC under the current operating plan; λ2 is the standard cost ratio for similar assets in year N2; λ3 is the standard cost ratio for similar assets in year N3;c0 is the initial investment cost, and r0 is the cost ratio of the production project.

where ALCC4 is the annual LCC value under the modernization plan; LCC4 is the LCC under the modernization plan; λ4 is the standard cost ratio for similar assets in year N4; P is the net value of the old asset, and C1 is the modernization project investment.

where ALCC5 is the annual LCC value under the overhaul plan; LCC5 is the LCC under the modernization plan; λ1 is the standard cost ratio for similar assets in year N1; λ5 is the standard cost ratio for similar assets in year (N1 - CN5), and C3 is the overhaul project investment.

5 Conclusions

In this study, we established an LCC analysis model and evaluation system for power plant equipment that can be used as a decision support model when procuring new assets or selecting equipment modernization and overhaul plans.The LCC analysis model was used to evaluate the equipment management options for a UHV power plant in the Southern China Power Grid in Guangzhou.The research results confirm the following.(1) Application of the LCC model facilitates efficient utilization of power plant equipment.LCC assessment of power equipment can be performed using an overall assessment model,where modernization and overhaul projects are evaluated based on multiple asset allocation.In this study, we used the fuzzy membership degree method.(2) Application of LCC theory can provide a scientific decision-making mechanism to facilitate equipment procurement and supplier management, and requires calculating the production input index for a certain type of equipment or supplier.(3) LCC assessment can support the decision-making process for selecting equipment modernization and overhaul projects.Comparing the LCC and average annual LCC of equipment modernization and overhaul plans, the most cost-effective plan facilitating long-term power plant operation and increasing economic benefits can be determined.

In the field of power equipment management, LCC theory can also be used:

(1) to prepare a standard operating cost database for power equipment and establish a scientific method to determine the operating and maintenance costs for different types of equipment and maintenance projects, allow for standardized management of operating and maintenance costs, and provide an effective tool for operation and maintenance evaluation.

(2) to conduct research on equipment scrapping strategies.A reasonable scrapping strategy can maximize the equipment value during its service life; strict control of the equipment scrapping rate can optimize the use of power plant assets based on scientific management.

(3) to conduct research on the overall cost management of an entire production project with the goal of identifying the lowest LCC, determined by analyzing the components in each stage of the project life-cycle.

(4) to conduct benchmark studies of asset management,where the calculated LCC of one power plant is compared with those of similar plants to determine areas for improvement based on the obtained LCC indexes, providing a method to address specific production problems.This method facilitates long-term development of power plants and increases their competitiveness.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (U1966210).

Declaration of Competing Interest

We declare that we have no conflict of interest.