Development of Redundancy Model for Co-generation Plant

First and foremost, the author would like to express his greatest gratitude to Allah for the success of this project. The author wishes Ir Dr. Mohd Amin bin Abd Majid for all the motivation, knowledge and advice given to complete this project. Thanks to his guidance and supervision, the author has learned and experienced a lot throughout the process.

Finally, the author would like to express his appreciation to Universiti Teknologi PETRONAS for providing the facilities and many learning opportunities, and to his family and friends who constantly support her throughout the journey to complete this project.

Background of Study

The annual value is used to analyze the impact of failure for redundancy using utilities and the generator set and the results were validated using low-level analysis.

Problem Statement

Objective

Scope of Study

LITERATURE REVIEW

Introduction of Cogeneration
Backup Power for Cogeneration Plant
Reliability and Availability
Annual Worth (AW) Analysis
Breakeven Analysis
Summary

The combined cycle of gas turbine and steam turbine consists of the combination of Brayton cycle and Rankine cycle. Normally, the gas turbine produces about 60% of the power while the remaining 40% is produced by steam turbine. The BAU case is the least that can be done to meet the thermal and electrical requirements of the system.

Both methods provide the power required to support the start-up of the CHP plant.

METHODOLOGY

Introduction
Data Acquisition
Reliability and Availability
Redundancy for Power Generation of Cogeneration System
Annual Worth Analysis
Breakeven Analysis
Project Gantt Chart

The cost of the generator set can be a product of one variable or of several variables, depending on the accuracy of the estimate. The estimated total annual costs of using public utilities are given by Total annual costs of using public utilities = {(Cost of repair per fault) + (Cost of. So the cost of electricity depends on the total hours of connection with public utilities and the amount of energy supplied.

Cr is the electricity price per kWh charged by public utility K is the capacity of the gas turbine in kW. Where Cgen is the capital cost of the generator set, A/P is an annual value factor for a specified amount of present value. A/F is the annual value factor for a stated amount of future value i is the interest rate n is the number of useful lives Co is the cost of annual operation.

The operating cost of using the aggregate is considered as the cost of fuel consumed by the unit during the outage of the cogeneration system. Previous studies have shown that the 20-year net present value of maintenance costs is approximately 10% of the unit cost [21]. Cgen is the capital cost of the generating set A/P is the annual value factor for the specified present value amount i is the interest rate n is the number of lifetimes.

In this study, the salvage value is estimated to be 20% of the capital cost of generator set [21] which ratio is given as. Where Csv is annualized recovery value of generator set Cgen is capital cost of generator set A/F is annual value factor for a stated amount of future value i is interest rate n is number of useful life.

Figure 3.1: Research methodology flowchart Identify cogeneration plant

RESULTS AND DISCUSION

Introduction

Spreadsheet

Below is the sample cost analysis spreadsheet shown in Figure 4.2 and the list of variables with the formula shown in Table 4.2. The data from the breakeven analysis will be used to generate graphs to determine the breakeven point. Alternative with lower annual cost will be chosen as the best alternative for this project.

Finally, the data calculated from the break-even analysis section will be used to generate a break-even chart.

Figure 4.1: Snapshot of data input section

Case study

To produce electricity, the plant used two units of 4.2 MW solar gas turbine generators. This plant operated 24 hours a day and was designed to operate with two turbines during peak hours and one turbine at night. Thermal accumulator 1 10,000 Rth thermal accumulator In order to increase the efficiency and reduce the economic losses of the device, it is important to analyze the efficiency of the device and compare the existing system with another alternative.

UTP-GDC installations can be divided into two main systems: a power generation system and a chilled water system. However, in this study, the author only analyzes the power generation system (PGS), as it depends on external electrical supply during a fault. The chilled water system, on the other hand, had an internal back-up, namely direct-fired chillers.

The use of electricity from external sources has an impact on the economic loss of the power plant. Thus, it is essential to study the power generation system of the UTP-GDC plant to increase the performance and reduce economic losses.

UTP-GDC power generation system (PGS)

Power Generation System (PGS) Performance Data …

In this level, the gas turbine is expected to operate in normal condition until maximum performance without fail. If the performance falls in the range of 1497 kW to 2851 kW, the turbine experiences reduced capacity due to minor faults in the system. This level is not critical as it can be restored to normal operating level by performing minor maintenance or repairs.

Finally, when the gas turbine capacity drops to 1497 kW or less, it is considered zero capacity. This is because a gas turbine at 1497 kW and below will stop because it is not efficient and will cause economic damage to the plant if it continues to operate. As can be seen from Table 4.6, the centriode of the zero capacity level is zero because no gas turbines are operating at this stage.

Gas turbine performance can be restored to normal operating condition through a major repair. During the repair phase, the UTP-GDC plant's power generation system will rely on the national power grid to provide electrical power to meet customer demand. The performance of the gas turbine over five years during the peak period from 10 a.m. to 5 p.m. is shown in Figure 4.7 below.

The normal operating level takes 78% of the total accumulated hours, followed by 18% for reduced capacity and 4% of the zero performance level. Thus, the average time in which the UTP-GDC plant purchased electricity from the national grid is 118.8 hours for each year.

Table 4.6: Performance level of UTP-GDC PGS [23]

Availability and Reliability

Mean time before failure (MTBF) and mean time to recovery (MTTR) were then calculated from the results of failure rate and recovery rate. After determining the MTBF and MTTR, the author then proceeds with availability and reliability of PGS from UTP-GDC plant. Gas turbines of UTP-GDC plant operate for 24 hours with both turbines operating during the day, especially during peak hours, and one turbine operating at night.

It takes a long time to repair the gas turbine as the failure considered for the zero efficiency stage was a major failure. Apart from that, the availability of power generation system is 0.98662 which is high as it is more than 0.95 which was determined as the reliability criterion of UTP-GDC power plant. Therefore, after 4300 operating hours, the probability of failure for this system is very high.

In order to replace existing redundancy with another alternative, the reliability of the new system must be greater than or equal to the previous method. Greater reliability of the system requires less maintenance and repairs, as the probability of failure is lower. MTU Onsite Energy Corp, on the other hand, claims that the generator is operating approximately 99.67 to 99.99 percent annually.

The national grid and the generator set have more or less the same system as both apply the N+1 system design. The reliability of PGS without redundancy, with national grid redundancy and with generation group redundancy was expressed in Figure 4.9.

Table 4.7: MTBF, MTTR, availability and reliability of UTP-GDC plant Mean Time before

Estimation of Gen Set Cost

Most of the generating sets were newly installed, which is suitable to be applied in this study as the author assumed that a new generating set would be installed for this project. The number of generators installed and the capacity of the site vary for each case depending on the needs of the area. After the data were collected, the author then developed the CER equation for single variable regression using linear and exponential type of relationship and bivariate regression model using SigmaPlot 11.0 software.

In the case of a single-variable regression model, the relationship between generator set costs and project size was studied. On the other hand, for the two-variable regression model, the number of gensets and the project size were taken as variables to determine the cost of gensets. The results in Figures 4.10 and 4.11 show that the cost of the generator set was above and below normal levels.

From the analysis of the graph, it can be observed that certain data can be considered unreliable as they do not follow the pattern. These case studies include the City of Fennimore, City of Garnett, City of Knoxville, City of Owensville, and South Plains EC with the highest percentage error of 65.79% recorded by South Plains EC. These five case studies deviated from the normal level of set costs as a result of projects being completed in a hurry.

The bivariate regression model has the lowest error rate compared to both univariate regression models. The error of the bivariate regression model is the lowest as it used more variables than the other models and thus produced more accurate results.

Table above showed 16 case studies from different areas in America. All the generators in the cases are diesel-fueled engines

Evaluation of Failure Consequences of PGS

The cost of peak demand charge contributes to 82% of the total cost of failure, 9% was the cost of electricity and 9% was the cost of repair. To reduce the cost of peak demand charging, the number of failures should be reduced by increasing the availability and reliability of the system. Therefore, by changing the redundancy of PGS, UTP-GDC plants can save an amount of RM every year.

The next step that the author applied in this study to select the best solution for the redundancy of the power generation system of the UTP-GDC plant was by using low-level analysis. As noted, the cost of the generator set is lower than that of utilities after 35.01 hours of operation. The redundancy decision was based on the number of plant hours.

For operating hours below 35.01 hours, the general supply is selected as redundancy. On the other hand, if it is greater than 35.01 hours, generator sets are a better alternative. Since the operating hours of the UTP-GDC were 121 hours, the generator set is therefore a better option as a redundancy for the power generation system.

Table 4.11: Cost of failure per year for UTP-GDC plant

CONCLUSION AND RECOMMENDATION

Conclusion

Recommendation

Availability model and economic impact of failure for a cogeneration plant subject to degradation and redundancy.