Back Up Power Systems

Table of Contents

1 INTRODUCTION

1.1 Pretext

1.2 Methods of Generating Electricity

1.3 Common Power Problems

2 BACK UP POWER SYSTEMS IN INDIA

2.1 Indian Scenario

2.2 Back-Up Power Systems

2.3 Classification of Back-Up Power Systems

2.4 Common BPSs

2.4.1 Commercially Used BPS in India

2.5 Significance of BPSs

2.6 Advantages of Diesel Gensets over Other BPS

2.7 Performance Parameters of Diesel Gensets

2.7.1 Generator Factors

2.7.2 Alternator Factors

2.8 Need for Optimization

2.6 Motivation of Study

3 BACKUP POWER SYSTEMS: A REVIEW

3.1 Power Crisis

3.2 Origin & Evolution of BPS

3.3 Process Improvement of BPS

3.4 Six Sigma in BPS

3.4.1 Case Study I

3.4.2 Case Study II

3.4.3 Case Study III

3.4.4 Case Study IV

3.4.5 Some More Case Studies

4 BACKUP POWER SYSTEMS & SIX SIGMA

4.1 Research Gap

4.2 Problem Formulation

4.3 Methodology Proposed

4.3.1 Define Phase

4.3.2 Measure Phase

4.3.3 Analyse Phase

4.3.4 Improve Phase

4.3.5 Control Phase

5 A CASE STUDY OF DIESEL GENSET

5.1 Define Phase

5.2 Measure Phase

5.3 Analyse Phase

5.4 Improve Phase

5.5 Control Phase

6 CONCLUSIONS AND FUTURE SCOPE

6.1 Conclusions

6.2 Scope for Future

Objectives and Thematic Focus

The primary objective of this work is to optimize the performance and operational mileage of diesel generators used as backup power systems within service organizations, utilizing the structured DMAIC (Define, Measure, Analyse, Improve, Control) methodology of Six Sigma to reduce power generation costs and equipment inefficiency.

• Application of Six Sigma business strategy for energy sector optimization.
• Comprehensive study of power crisis issues and the dependency on backup power systems.
• Implementation of the DMAIC model to identify and improve critical process parameters.
• Parametric optimization of diesel generator performance to maximize energy efficiency.
• Reduction of power generation costs and overall operational expenditures.

Excerpt from the Book

Summary of Chapters

1 INTRODUCTION: This chapter introduces the increasing demand for backup power systems due to electricity shortages and outlines the research objective of optimizing generator mileage.

2 BACK UP POWER SYSTEMS IN INDIA: This chapter provides an overview of the power landscape in India, the types of backup systems in use, and the performance parameters crucial for generator maintenance.

3 BACKUP POWER SYSTEMS: A REVIEW: This chapter reviews existing literature on energy crises and investigates how various industries have applied Six Sigma and other improvement methodologies to their power systems.

4 BACKUP POWER SYSTEMS & SIX SIGMA: This chapter identifies the research gap regarding optimization in the BPS sector and proposes the DMAIC framework as a structured solution for performance improvement.

5 A CASE STUDY OF DIESEL GENSET: This chapter documents the practical implementation of the DMAIC methodology on a 320 KVA diesel generator, including data analysis, experimentation, and subsequent performance optimization.

6 CONCLUSIONS AND FUTURE SCOPE: This chapter summarizes the research findings on Six Sigma’s effectiveness in reducing backup power costs and discusses future applications in micro-grids and other infrastructure areas.

Keywords

Six Sigma, DMAIC, Diesel Generator, Genset, Backup Power System, BPS, Energy Optimization, Mileage, Performance Improvement, Operational Cost, Power Crisis, Quality Management, Efficiency, DOE, Reliability.

Frequently Asked Questions

What is the core focus of this research?

The research focuses on implementing the Six Sigma DMAIC methodology to optimize the fuel efficiency and overall mileage of diesel generators used as backup power systems in organizations.

Which industry sectors are considered the primary focus?

The book primarily focuses on service organizations and institutional settings that rely on diesel generators for continuous power during utility outages.

What is the primary objective of the case study?

The main objective is to identify critical operating parameters—specifically coolant temperature, lube oil pressure, and load—and optimize them to enhance the energy generation efficiency of a 320 KVA diesel Genset.

Which methodology is employed for optimization?

The study utilizes the DMAIC (Define, Measure, Analyse, Improve, Control) model, supported by statistical tools like ANOVA, Pareto charts, and Design of Experiments (DOE).

What key findings are highlighted in the book?

The study found that by optimizing process variables, the mean mileage of the Genset could be significantly improved, resulting in approximately 32.57% in monetary savings.

How are the results of the Six Sigma approach validated?

Validation is achieved through an extensive 12-month case study, comparing historical performance data with performance metrics after the implementation of optimized settings.

How does seasonal change affect the performance of the Genset?

The research observes that ambient conditions, particularly seasonal variations between winter and summer, significantly impact the mileage performance of outdoor-placed generators.

What is the role of the Response Optimizer in this study?

The Response Optimizer tool in Minitab is used to forecast the ideal settings for input factors that jointly maximize the mileage output of the generator.