112,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
Exploring methods and techniques to optimize processing energy efficiency in process plants, Energy and Process Optimization for the Process Industries provides a holistic approach that considers optimizing process conditions, changing process flowschemes, modifying equipment internals, and upgrading process technology that has already been used in a process plant with success. Field tested by numerous operating plants, the book describes technical solutions to reduce energy consumption leading to significant returns on capital and includes an 8-point Guidelines for Success. The book provides managers, chemical and mechanical engineers, and plant operators with methods and tools for continuous energy and process improvements.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 772
Veröffentlichungsjahr: 2013
Ähnliche
Contents
Cover
Title Page
Copyright
Dedication
Preface
Part 1: Basic Concepts and Theory
Chapter 1: Overview of this Book
1.1 Introduction
1.2 Who is this Book Written for?
1.3 Five Ways to Improve Energy Efficiency
1.4 Four Key Elements for Continuous Improvement
1.5 Promoting Improvement Ideas in the Organization
Chapter 2: Theory of Energy Intensity
2.1 Introduction
2.2 Definition of Process Energy Intensity
2.3 The Concept of Fuel Equivalent (FE)
2.4 Energy Intensity for a Total Site
2.5 Concluding Remarks
Nomenclature
References
Chapter 3: Benchmarking Energy Intensity
3.1 Introduction
3.2 Data Extraction from Historian
3.3 Convert All Energy Usage to Fuel Equivalent
3.4 Energy Balance
3.5 Fuel Equivalent for Steam and Power
3.6 Energy Performance Index (EPI) Method
3.7 Concluding Remarks
Nomenclature
Reference
Chapter 4: Key Indicators and Targets
4.1 Introduction
4.2 Key Indicators Represent Operation Opportunities
4.3 Define Key Indicators
4.4 Set Up Targets For Key Indicators
4.5 Economic Evaluation for Key Indicators
4.6 Application 1: Implementing Key Indicators Into an “Energy Dashboard”
4.7 Application 2: Implementing Key Indicators to Controllers
4.8 It is Worth The Effort
Nomenclature
References
Part 2: Energy System Assessment Methods
Chapter 5: Fired Heater Assessment
5.1 Introduction
5.2 Fired Heater Design for High Reliability
5.3 Fired Heater Operation for High Reliability
5.4 Efficient Fired Heater Operation
5.5 Fired Heater Revamp
Nomenclature
References
Chapter 6: Heat Exchanger Performance Assessment
6.1 Introduction
6.2 Basic Concepts and Calculations
6.3 Understand Performance Criterion—U Values
6.4 Understanding Pressure Drop
6.5 Heat Exchanger Rating Assessment
6.6 Improving Heat Exchanger Performance
Appendix: TEMA Types of Heat Exchangers
Nomenclature
References
Chapter 7: Heat Exchanger Fouling Assessment
7.1 Introduction
7.2 Fouling Mechanisms
7.3 Fouling Mitigation
7.4 Fouling Mitigation for Crude Preheat Train
7.5 Fouling Resistance Calculations
7.6 A Cost-Based Model for Clean Cycle Optimization
7.7 Revised Model for Clean Cycle Optimization
7.8 A Practical Method for Clean Cycle Optimization
7.9 Putting All Together—A Practical Example of Fouling Mitigation
Nomenclature
References
Chapter 8: Energy Loss Assessment
8.1 Introduction
8.2 Energy Loss Audit
8.3 Energy Loss Audit Results
8.4 Energy Loss Evaluation
8.5 Brainstorming
8.6 Energy Audit Report
Nomenclature
References
Chapter 9: Process Heat Recovery Targeting Assessment
9.1 Introduction
9.2 Data Extraction
9.3 Composite Curves
9.4 Basic Concepts
9.5 Energy Targeting
9.6 Pinch Golden Rules
9.7 Cost Targeting: Determine Optimal ΔTmin
9.8 Case Study
9.9 Avoid Suboptimal Solutions
9.10 Integrated Cost Targeting and Process Design
9.11 Challenges for Applying the Systematic Design Approach
Nomenclature
References
Chapter 10: Process Heat Recovery Modification Assessment
10.1 Introduction
10.2 Network Pinch—the Bottleneck of Existing Heat Recovery System
10.3 Identification of Modifications
10.4 Automated Network Pinch Retrofit Approach
10.5 Case Studies for Applying the Network Pinch Retrofit Approach
References
Chapter 11: Process Integration Opportunity Assessment
11.1 Introduction
11.2 Definition of Process Integration
11.3 Plus and Minus (+/−) Principle
11.4 Grand Composite Curves
11.5 Appropriate Placement Principle for Process Changes
11.6 Examples of Process Changes
References
Part 3: Process System Assessment and Optimization
Chapter 12: Distillation Operating Window
12.1 Introduction
12.2 What is Distillation?
12.3 Distillation Efficiency
12.4 Definition of Feasible Operating Window
12.5 Understanding Operating Window
12.6 Typical Capacity Limits
12.7 Effects of Design Parameters
12.8 Design Checklist
12.9 Example Calculations for Developing Operating Window
12.10 Concluding Remarks
Nomenclature
References
Chapter 13: Distillation System Assessment
13.1 Introduction
13.2 Define a Base Case
13.3 Calculations for Missing and Incomplete Data
13.4 Building Process Simulation
13.5 Heat and Material Balance Assessment
13.6 Tower Efficiency Assessment
13.7 Operating Profile Assessment
13.8 Tower Rating Assessment
13.9 Column Heat Integration Assessment
13.10 Guidelines for Reuse of an Existing Tower
Nomenclature
References
Chapter 14: Distillation System Optimization
14.1 Introduction
14.2 Tower Optimization Basics
14.3 Energy Optimization For Distillation System
14.4 Overall Process Optimization
14.5 Concluding Remarks
References
Part 4: Utility System Assessment and Optimization
Chapter 15: Modeling of Steam and Power System
15.1 Introduction
15.2 Boiler
15.3 Deaerator
15.4 Steam Turbine
15.5 Gas Turbine
15.6 Letdown Valve
15.7 Steam Desuperheater
15.8 Steam Flash Drum
15.9 Steam Trap
15.10 Steam Distribution Losses
Nomenclature
References
Chapter 16: Establishing Steam Balances
16.1 Introduction
16.2 Guidelines for Generating Steam Balance
16.3 A Working Example for Generating Steam Balance
16.4 A Practical Example for Generating Steam Balance
16.5 Verify Steam Balance
16.6 Concluding Remarks
Nomenclature
Reference
Chapter 17: Determining True Steam Prices
17.1 Introduction
17.2 The Cost of Steam Generation from Boiler
17.3 Enthalpy-Based Steam Pricing
17.4 Work-Based Steam Pricing
17.5 Fuel Equivalent-Based Steam Pricing
17.6 Cost-Based Steam Pricing
17.7 Comparison of Different Steam Pricing Methods
17.8 Marginal Steam Pricing
17.9 Effects Of Condensate Recovery On Steam Cost
17.10 Concluding Remarks
Nomenclature
References
Chapter 18: Benchmarking Steam System Performance
18.1 Introduction
18.2 Benchmark Steam Cost: Minimize Generation Cost
18.3 Benchmark Steam and Condensate Losses
18.4 Benchmark Process Steam Usage and Energy Cost Allocation
18.5 Benchmarking Steam System Operation
18.6 Benchmarking Steam System Efficiency
Nomenclature
References
Chapter 19: Steam and Power Optimization
19.1 Introduction
19.2 Optimizing Steam Header Pressure
19.3 Optimizing Steam Equipment Loadings
19.4 Optimizing On-Site Power Generation Versus Power Import
19.5 Minimizing Steam Letdowns and Venting
19.6 Optimizing Steam System Configuration
19.7 Developing Steam System Optimization Model
Nomenclature
Reference
Part 5: Retrofit Project Evaluation and Implementation
Chapter 20: Determine the True Benefit from the OSBL Context
20.1 Introduction
20.2 Energy Improvement Options Under Evaluation
20.3 A Method for Evaluating Energy Improvement Options
20.4 Feasibility Assessment and Make Decisions for Implementation
Chapter 21: Determine the True Benefit From Process Variations
21.1 Introduction
21.2 Collect Online Data for the Whole Operation Cycle
21.3 Normal Distribution and Monte Carlo Simulation
21.4 Basic Statistics Summary for Normal Distribution
Nomenclature
Reference
Chapter 22: Revamp Feasibility Assessment
22.1 Introduction
22.2 Scope and Stages of Feasibility Assessment
22.3 Feasibility Assessment Methodology
22.4 Get the Project Basis and Data Right in the Very Beginning
22.5 Get Project Economics Right
22.6 Do Not Forget OSBL Costs
22.7 Squeeze Capacity Out of Design Margin
22.8 Identify and Relax Plant Constraints
22.9 Interactions Between Process Conditions, Yields, and Equipment
22.10 Do Not Get Misled by False Balances
22.11 Prepare for Fuel Gas Long
22.12 Two Retrofit Cases for Shifting Bottlenecks
22.13 Concluding Remarks
Nomenclature
References
Chapter 23: Create an Optimization Culture with Measurable Results
23.1 Introduction
23.2 Site-Wide Energy Optimization Strategy
23.3 Case Study of the Site-Wide Energy Optimization Strategy
23.4 Establishing Energy Management System
23.5 Energy Operation Management
23.6 Energy Project Management
23.7 An Overall Work Process from Idea Discovery to Implementation
References
Index
Copyright © 2014 by the American Institute of Chemical Engineers, Inc.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey. All rights reserved
Published simultaneously in Canada
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at www.wiley.com/go/permission.
Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002.
Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com.
Library of Congress Cataloging-in-Publication Data:
Zhu, Frank Xin X.
Energy optimization for the process industries/Frank Xin X. Zhu. – Firstedition.
pages cm
Includes index.
ISBN 978-1-118-10116-2 (hardback)
1. Process engineering. 2. Manufacturing processes–Cost control. 3. Manufacturing processes–Environmental aspects. 4. Energy conservation. I. Title.
TS176.Z53 2013
658.5–dc23
2013020443
To Jane, Kathy, and JoshuaThese three remain: faith, hope, and love.The greatest of these is love.1 Corinthians 13:13
Preface
In recent years, there has been an increased emphasis on industrial energy optimization. However, there are no dedicated books available to discuss basic concepts, provide practical methods, and explain industrial application procedures. This book is written to fill this gap with the following people in mind: managers, engineers, and operators working in the process industries. The book is aimed at providing practical tools to people who face challenges and wish to find opportunities for improved processing energy efficiency. I hope that this book is able to convey concepts, theories, and methods in a straightforward and practical manner.
With these objectives in mind, the focal discussions in this book center around five kinds of energy improvement opportunities. The first is minimizing heat losses via diligence. In reality, steam generated in the boiler house is distributed through an extensive network of steam pipelines to end users. The losses in steam distribution can be 10–20% of fuel fired in boilers. Hence, the net boiler efficiency could be 10–20% lower from the user's point of view.
The second is operation improvement opportunities, which occur due to the age of processes, the nature of operation variations. This usually involves establishing the best operation practices and optimizing process conditions. The third opportunity comes from improved heat recovery within and across process units, which requires design changes to process flow schemes and heat exchange schemes. The fourth is the use of state-of-the-art processes and equipment technology for enhanced processing efficiency. The fifth and final opportunity comes from better operation and planning of the energy supply system. In this book, these opportunities will be discussed and the methods for opportunity identification, assessment, and implementation will be introduced.
As the book covers a wide range of topics, I have attempted to organize the materials in such a way that aids the reader to locate the relevant materials quickly, to be able to understand them readily, and to apply them in the right context. Furthermore, the structure of the book is carefully designed to help readers avoid losing sight of the forest for the trees. The book starts with a provision of an overall context of the process energy optimization, followed by concepts and theory to gain a basic understanding of the energy metrics, gradually transitions to practical assessment methods from equipment- to system-based evaluations, and culminates in establishing an effective energy management system to sustain the benefits. Therefore, the features of material organizations need to be explained:
An overview of process energy optimization is provided in Chapter 1. Basic concepts for process energy efficiency are introduced in Chapters 2–4 in Part 1. These concepts include energy intensity for determining process-specific energy use, energy benchmarking for setting the energy baseline and identifying the improvement gap, and key energy indicators for determining what operating parameters to monitor and what are their operating targets.Energy assessment methods are presented in Part 2. Chapter 5 focuses on reliable and efficient operation for process-fired heaters, while Chapter 6 discusses process energy loss analysis. Chapters 7 and 8 are dedicated to heat exchanger performance assessment as well as fouling mitigation. Methods for heat recovery targeting and retrofit design are explained in Chapters 9 and 10, while process integration methods are illustrated in Chapter 11.Part 3 is dedicated to process assessment. The concept of operating window for fractionation is introduced in Chapter 12 where the calculation methods for determining the operating window are explained. Fractionation system assessment and optimization are discussed in Chapters 13 and 14.The steam and power system must supply energy in an efficient manner if one wishes to achieve high energy efficiency for an overall processing site. Thus, methods for steam and power system assessment and optimization are provided in Part 4. Steam and power system modeling is explained in Chapter 15. Chapter 16 covers steam and power balances. Chapter 17 discusses practical steam pricing methods. Chapter 18 focuses on steam system benchmarking. By putting the models and opportunities together, Chapter 19 discusses how to build mathematical models for steam and power optimization.Finally, Part 5 is dedicated to techno-economical analysis of energy modifications as well as establishing an effective energy management system. To avoid bad investment, true benefits must be determined by considering outside system battery limit conditions and process variations, which are discussed in Chapters 20 and 21. The goal of the capital project evaluation is to achieve minimum investment cost. The key to achieving this goal is to explore alternative design options for each improvement idea and find economical solutions to overcome process/equipment limits. Detailed discussions are given in Chapter 22. The last chapter, Chapter 23, condenses the ideas presented in the other chapters by explaining how to establish an effective energy management system to sustain the benefits gained from implementation through a case study.It is my sincere hope that readers will find the methods and techniques discussed herein useful for analysis, optimization, engineering design, and monitoring, which are required to identify, assess, implement, and sustain energy improvement opportunities. More importantly, I hope that this book can help readers build mental models in terms of key parameters and their limits and interactions. You can then revisit these methods whenever you need them.
Clearly, it was not a small effort to write this book; but it was the strong need of practical methods for helping people to improving industrial energy efficiency that spurred me to writing. In this endeavor, I owe an enormous debt of gratitude to many colleagues at UOP and Honeywell for their generous support to this effort. First of all, I would like to mention Geoff Miller, vice president of UOP, who has provided encouragement and support. I am very grateful to many colleagues for constructive suggestions and comments on the materials contained in this book, and I apologize if any names are unmentioned. I would especially like to thank John Petri for his critical readings of Chapter 4, Darren Le Geyt and Dennis Clary for Chapter 5, Phil Daly and Lillian Huppler for Chapter 6, Zhanping (Ping) Xu for Chapter 12, and Chuck Welch for Chapter 15; their comments have improved these chapters. Tom King provided meticulous line-by-line reading of the entire first draft and identified pedagogical lapses, typos, better expressions, and better sources of information. My sincere gratitude also goes to Charles Griswold, Margaret (Peg) Stine, and Mark James for their review of the book. I would like to thank all of my colleagues for their help with the book and my debt to them is very great, but I would like to stress that any deficiencies are my responsibility. This book reflects my own opinions and not that of UOP and Honeywell.
I would also like to thank my co-publishers, AIChE and John Wiley, for their help. Special thanks go to Steve Smith at AIChE and Michael Leventhal at John Wiley for guidance. The copyediting and typesetting by Vibhu Dubey at Thomson Digital is very helpful in polishing the book.
Finally, I am truly grateful to my family: my wife Jane and my children Kathy and Joshua, for their understanding, unwavering support, and generosity of spirit in tolerating the absentee paterfamilias during the writing of this book. Jane, my beloved wife, produced beautiful drawings for many figures in the book with her graphic design skills and Kathy helped to polish this book with her linguistic skills. Your contributions to this book and to my life are deeply appreciated.
Frank Zhu
Long Grove, Illinois, USAMay 7, 2013
Part 1
Basic Concepts and Theory
1
Overview of this Book
1.1 Introduction
Energy management is a buzzword nowadays. What is the objective of energy management in the process industry? It is not simply energy minimization. The ultimate goal of energy management is to control energy usage in the most efficient manner to make production more economical and efficient. To achieve this goal, energy use must be optimized with the same rigor as how product yields and process safety are managed.
The time of “let the plant engineers do their technical work” is long gone. The reduction of the technical workforce due to automation and technology advances has also increased the level of responsibility on business management of plant operations, often resulting in fewer workers taking on more tasks. Furthermore, it is often the case that plant managers and engineers are ill-prepared to take on widespread responsibilities, particularly when working under time pressures. This in turn results in their devoting less time on plant operation and equipment reliability and maintenance. Therefore, the current challenge for energy optimization is: How can we develop effective enablers to support engineers and management?
In addition, plant management and engineers are presented with modern management concepts and techniques. Not all these methods are easily translatable or applicable to any given company. Even if implemented, some of these methods require tailor-made revisions to fit into specific applications. The challenge here becomes: Which methods should be selected and how to implement them for specific circumstances?
This reminds me of a project I led a few years into the new millennium. My company took on a project to provide technical support to a large oil refining plant and I was tasked with leading a team of engineers to spearhead this effort. When I met with the general manager of the refinery plant, his words were brief. “My plant spends huge amounts of money on operating costs, in the order of hundreds of million dollars per year.” The general manager started after a quick introduction. “I know someone out there can help my plant to cut down the energy cost by more than 10%. I hope it is you.” These simple words from the general manager became a strong motivation like a heavy weight on my shoulder. I took the challenge and worked with the team and the plant staff to achieve the goal. By the end of the fifth year, a survey team from corporate management came on site. After reviewing the data and various utility costs, the team issued the statement that the plant had achieved the corporate goal of saving 10% energy costs. Our efforts were successful and the results were recognized by the plant and corporate management.
Over time, I applied the methods and tools I had developed over the course of my career to other projects I was staffed on in the past 10 years. The theory and practice of these methods and experience has become the foundation of this book. The book will present the core of a systematic approach covering energy optimization strategy, solution methodology, supporting structure, and assessment methods. In short, it will describe what it takes to make sizable reductions in energy operating costs for process plants and how to sustain energy-saving benefits. The benefits of this effective approach include identification of large energy-saving projects via applying assessment methods, capturing hidden opportunities in process operation via use of key energy indicators, closing of various loose ends in steam system and off-site utilities via good steam balances, optimizing utility system operation via setting up appropriate steam prices, and maintaining continuous improvement via regular review and performance matrices.
The concepts, methods, and tools presented in this book provide a glimpse of recent advances in energy utilization techniques based on simultaneous optimization of process and energy considerations. The case studies show that very substantial improvements in energy utilization can be made by applying these methods and tools not only in new investment projects but also in existing plants.
1.2 Who is this Book Written for?
This book is written with the following people in mind: managers, engineers, and operators working in the process industries who face challenges and wish to find opportunities for improved processing energy efficiency and are searching for tools for better energy management.
It is my hope that readers are able to take away methods and techniques for analysis, optimization, engineering design, and monitoring, which are required to identify, assess, implement, and sustain energy improvement opportunities. The analysis methods are used for energy benchmarking and gap assessment, while optimization methods are used for operation improvement, heat integration, process changes, and utility system optimization. Engineering methods are applied for developing energy revamp projects, while monitoring methods are used for establishing energy management systems. More importantly, I would like to help readers to build mental models for critical equipment and processes in terms of key parameters and their limits and interactions. You can then revisit these models whenever you need them.
1.3 Five Ways to Improve Energy Efficiency
The five ways in which improved energy efficiency can be achieved within plant processes are highlighted below and will be discussed in detail in this book:
Minimizing wastes and lossesOptimizing process operationAchieving better heat recoveryDetermining process changesOptimizing energy supply system1.3.1 Minimize Waste and Losses
In reality, steam generated in the boiler house is distributed through an extensive network of steam pipelines to end users. The losses in steam distribution can be 10–20% of fuel fired in boilers. Hence, the net boiler efficiency could be 10–20% lower from the user's point of view.
The losses do not necessarily attribute to a single cause but are the result of a combination of various causes. It is common to observe the major steam loss caused by steam trap failure and condensate discharge problems. Steam loss could also occur due to poor insulation of steam pipes, leaks through flanges and valve seals, opened bypass and/or bleeder valves, and so on. Simple measures such as maintenance of steam traps and monitoring of steam distribution to determine if steam generated is in accordance with steam consumed can lead to significant cost-saving benefits.
Apart from distribution losses, other forms of energy losses could occur due to poor insulation, condensate loss to drainage, pressure loss from steam letdown through valves, pump spill backs, and so on. To detect losses, you must know how much energy is generated versus how much is used in individual processes. The benchmarking method in Chapter 3 could be used to determine the overall gap of the energy performance, and individual losses are identified using different methods. Process energy losses can be detected using the energy loss assessment methods discussed in Chapter 8, while identification of steam losses and the ways to overcome the losses in the steam system are discussed in Chapter 18.
1.3.2 Optimizing Process Operation
The most important step in developing an energy management solution to optimize a process is to be able to measure what process performance looks like against a reasonable set of benchmarks. This involves capturing energy data related to the process and organizing it in a way that allows operations to quickly identify where the big energy consumers are and how well they are doing against a consumption target that reflects the current operations. Only then is it possible to do some analysis to determine the cause of deviations from target and take appropriate remedial action. For this purpose, the concept of key energy indicators is introduced in Chapter 4.
The operation performance gaps are mainly caused by operation variability. Two kinds of operation variability are common in the industry. The first is the so-called operation inconsistency, which is mainly caused by different operation policy and practices applied due to different experience from operators. The second operation inefficiency refers to the kind of operation that is consistent but nonoptimal. This occurs when there are no tools available to indicate to the shift operators the optimal method to run the process and equipment when conditions of feeds and product yields vary.
Once operational gaps are identified, assessment methods (Chapters 5–8 for energy operation, Chapters 12 and 13 for process operation, and Chapter 16 for utility system operation) are then applied to identify root causes—potential causes include inefficient process operation, insufficient maintenance, inadequate operating practices, procedures, and control, inefficient energy system design, and outdated technology. Assessment results are translated into specific corrective actions to achieve targets via either manual adjustments, the best practices, or by automatic control systems. Finally, the results are tracked to measure the improvements and benefits achieved.
1.3.3 Achieving Better Heat Recovery
Using monitoring and optimization tools to improve energy efficiency usually results in pushing the process up against multiple physical constraints. To reach the next level of energy efficiency requires capital cost modifications to increase heat recovery within and across process units. One of the key values of implementing operational solutions first is that it can clearly highlight where the physical constraints exist to the process.
Once specific process units have been identified for improved heat integration, pinch technology can be applied to efficiently screen potential modification options, which is explained in Chapter 9. Practical assessment (Chapter 10) is required, which considers not only the value and cost of improved heat recovery but also the impact in terms of operating flexibility, especially with respect to start-up, shutdown, maintenance, control, and safety.
1.3.4 Determining Process Changes
Improved heat recovery is the most common type of capital projects implemented to improve energy efficiency. However, the use of advanced process/equipment technology may provide significant opportunities. Many of these areas make use of advanced process technology, such as enhanced heat exchangers, high-capacity fractionator internals, dividing wall columns, new reactor internals, power recovery turbines, improved catalysts, and other design features.
There are a variety of advanced technologies that can be applied, all of which vary in terms of implementation cost and return on investment. Careful evaluation of each of these solutions is required to select only the best opportunities that provide the highest return on the capital employed. Chapter 11 provides directions and principles for making process changes.
1.3.5 Optimizing Energy Supply System
In addition to using energy more efficiently in the process, another common strategy is to produce energy more efficiently. Many plants have their own on-site power plants that primarily exist to provide steam and power to the process units, but may also supply electricity to the grid when electricity price is high.
Energy supply optimization is achieved by optimizing the configuration and operating profiles of the boilers and turbines to meet energy demand while taking into account tiered pricing for power and natural gas, power contracts to the grid while meeting environmental limits on NOx and CO2 emissions. Energy supply optimization is discussed in Chapter 19.
1.4 Four Key Elements for Continuous Improvement
An effective energy optimization consists of four key elements: target setting, measuring, gap identification, and implementation. Achieving continuous energy improvement occurs only when all these four elements are working in good order as shown in Figure 1.1.
Figure 1.1 Four elements of energy management system.
The energy targeting implies setting up a base line energy performance against which actual energy performance can be compared. The base line energy performance should take into account the production rate and processing severity. The ratio of actual performance and base line performance is the energy performance indicator for a process area and an overall plant. The base line energy performance becomes the energy guideline or target for operation. For the energy target to be practical, it must be achievable based on equipment integrity, technology capability, availability of required tools, and skills.
1.5 Promoting Improvement Ideas in the Organization
As a technical manager or process engineer or operator, you may have already acquired some good ideas for improving your plant and process unit. However, it is not an easy feat to persuade the technical committee to consider your ideas and then proceed to accept and eventually implement them. I have observed many good ideas that have died in the infancy stage because they could not pass the evaluation gates. Such failure is commonly due to a lack of techno-economic assessment and communications. Remember, it is always necessary to sell your ideas to key stakeholders.
First, you need to develop technical and economic merits to build a business case. Therefore, it is imperative that you determine the benefit of your ideas, that is, what is the value to the stakeholders, in the very early stages. Next, you should identify, with the help of process specialists, what it takes to implement the idea. You need to do the necessary homework to come up with rough estimates of the capital cost required to deliver the benefit for your ideas.
If the benefit outweighs the cost significantly, it is then necessary to elicit comments and feedback from technical specialists in the areas of operation, engineering, maintenance, and control. Their feedback will provide additional insights for the feasibility of implementing your ideas. Several review meetings may be required during idea development and assessment. Try to limit the scope of these meetings with highly selective attendees because a focused meeting could allow in-depth discussions leading to idea expansion and improvements. In the end, a thorough safety review is essential.
Once you pass reviews based on technical merits, you need to sell your ideas to get buy-in from management. Although management expresses a strong voice for supporting energy efficiency improvement, management will not provide a blank check. You should remember the fact that the business objective of your plant is to produce desirable products and realize targeted economic margins. To successfully convince management, you need to connect your ideas with key business drivers.
In the chapters that follow, all the essential tools will be provided in a clear, step-by-step manner together with application examples. My hope is that by applying the methods in your work—one step at a time, whether you are a manager, an engineer, or an operator—it will enable you to discover improvement ideas, to asses them, and then finally to prioritize them in a good order. Once all these boxes are checked, you will have a good chance to communicate and implement your ideas successfully within your organization.
2
Theory of Energy Intensity
Management's vision and intent is not good enough to achieve energy improvements. Technical concepts and targets must be used as the basis for measuring and improving process energy efficiency. Energy intensity is one of the key technical concepts as it lays down the foundation for process energy benchmarking.
2.1 Introduction
In some industrial plants, energy optimization work falls into no-man's land. If you ask process engineers, supervisors, and operators, they will tell you that they have done everything they can in making their process units energy efficient. It is understandable that technical people feel proud of themselves in trying to do their job right. If you ask plant managers, they may tell you everything is in good order.
The truth of the matter is that there is large room for energy efficiency improvement. To find out the truth, you may ask a few questions: What metrics are applied to measure the process energy efficiency? What energy indicators are defined for the key equipment? How do you set up targets for these indicators?
The answers to these three questions will show if the plant management only stays in good intention but without proper measures in place. If no energy metrics are used to measure performance level and no indicators are applied for major equipment and no targets are employed for identifying improvements, the energy management program is only on the basis of good intent. It is possible to get people motivated with good intention. However, the motivation will decline gradually if people do not know what to do and have no directions.
To overcome this shortfall, two key concepts are introduced, namely, energy intensity and key energy indicators. The concept of energy intensity sets the basis for measuring energy performance, while the concept of key energy indicators provides guidance for what to do and how. Both energy intensity and key indicators are the cornerstones of an effective and sustainable energy management system. Energy intensity is introduced in this chapter, while example calculations for energy intensity are given in Chapter 3. The concept of key indicators will be discussed in Chapter 4.
2.2 Definition of Process Energy Intensity
Meaning must transfer to correct concepts and then concepts must be expressed in mathematical forms for the meaning to be precise and measurable for industrial applications. Adjectives like excellent, good, and bad, have no quantifiable values for technical applications because they cannot be measured. Thus, we need a clear definition of mere linguistic terms from management intent to make sustainable energy performance improvement. In other words, we need to have an operational definition of process energy performance that everyone can agree on and relate to and act upon.
Let us start with the specific question: how to define energy performance for a process? People might think of energy efficiency first. Although energy efficiency is a good measure as everyone knows what it is about, it does not relate energy use to process feed rate and yields, and thus it is hard to connect the concept of energy efficiency to plant managers and engineers.
To overcome this shortcoming, the concept of energy intensity is adopted, which connects process energy use and production activity. The energy intensity originated from Schipper et al. (1992a, 1992b), who attempted to address the intensity of energy use by coupling energy use and economic activity through the energy use history in five nations: the United States, Norway, Denmark, Germany, and Japan. The concept of energy intensity allows them to better examine the trends that prevailed during both increasing and decreasing energy prices.
By definition, energy intensity (I) is described by
(2.1)
Total energy use (E) becomes the numerator, while common measure of activity (A) is the denominator. For example, commonly used measures of activity are vehicle miles for passenger cars in transportation, kWh of electricity produced in the power industry, and unit of production for the process industry, respectively.
Physical unit of production can be t/h or m3/h of total feed (or product). Thus, industrial energy intensity can be defined as
(2.2)
Energy intensity defined in equation (2.2) directly connects energy use to production as it puts production as the basis (denominator). In this way, energy use is measured on the basis of production, which is in the right direction of thought: a process is meant to produce products supported by energy. For a given process, energy intensity has a strong correlation with energy efficiency. Directionally, efficiency improvements in processes and equipment can contribute to observed changes in energy intensity.
Therefore, we can come to agree that energy intensity is a more general concept for measuring of process energy efficiency indirectly.
Before adopting the concept of energy intensity, you may ask the question: Which one, feed rate or product rate, should be used as the measure of activity? For plants with a single most desirable product, the measure of activity should be product. For plants making multiple products, it is better to use feed rate as the measure of activity. The explanation is that a process may produce multiple products and some products are more desirable than others in terms of market value. Furthermore, some products require more energy to make than others. Thus, it could be very difficult to differentiate products for energy use. If we simply add all products together for the sum to appear in the denominator in equation (2.2), we encounter a problem, which is the dissimilarity in product as discussed. However, if feed is used in the denominator, the dissimilarity problem is nonexistent for cases with single feed, and the dissimilarity is much less a concern for multiple feed cases than for multiple products because, in general, feeds are much similar in composition than products.
The above discussions lead us to define the process energy intensity on the feed basis as
(2.3)
It is straightforward to calculate the energy intensity for a process using equation (2.3) where E is the total net energy use and F is the total fresh feed entering the process. Net energy use is the difference of total energy use and total energy generation. Process energy use mainly includes fuel fired in furnaces, steam consumed in column stripping and reboiling as well as steam turbines as process drivers, and electricity for motors. Process energy generation mainly comes from process steam generation, and power generation. In many cases, a process makes fuel gas and/or fuel oil, which are exported to other processes for firing or sold to markets. This type of fuel is not counted as energy generation as it is regarded as a part of product slates.
2.3 The Concept of Fuel Equivalent (FE)
There is an issue yet to be resolved for the energy intensity defined in equation (2.3). The energy use (E) for a process consists of fuel, steam, and electricity. They are not additive because they are different in energy forms and quality. However, if these energy forms can be traced back to fuel fired at the source of generation, which is the meaning of fuel equivalent (FE), they can be compared on the same basis, which is fuel. In other words, they can be added or subtracted after being converted to their fuel equivalent. For simplicity of discussions, definitions of FE for different energy forms are given here, while examples of FE calculations are provided in Chapter 3.
In general, FE can be defined as the amount of fuel fired (Qfuel) at the source to make a certain amount of energy utility (Gi):
(2.4)
In most cases, Qfuel is calculated based on the lower heating value of fuel. Gi is quantified in different units according to specifications in the marketplace, namely, Btu/h for fuel, lb/h for steam, and kWh for power. Thus, specific FE factors can be developed as follows based on this general definition of fuel equivalent. Energy are required for making boiler feed water (BFW), condensate and cooling water. The FE factors for these utilities will be discussed in Chapter 3.
2.3.1 FE Factors for Fuel
By default, fuel is the energy source. No matter what different fuels are used, tracing back to itself makes “fuel equivalent for fuel” equal to unity:
(2.5)
2.3.2 FE Factors for Steam
A typical process plant has multiple steam headers, typically designated as high, medium, and low pressure. In some cases, very high pressure steam is generated in boilers, which is mainly used for power generation. For calculating the fuel equivalent of steam, a top–down approach is adopted starting from steam generators. The total FE for each steam header is the summation of all FEs entering the steam header via different steam flow paths, which include steam generated from on-purpose boilers and waste heat boilers, steam from turbine exhaust, steam from pressure letdown valves, and so on. The FE for each steam header is the total FE divided by the amount of steam generated from this header:
(2.6)
2.3.3 FE Factors for Power
For power, FEpower is expressed as
(2.7)
where ηcycle is the cycle efficiency of power generation and Qpower represents the amount of heat content associated with power in unit of Btu/h.
By using the conversion factor of 1 kW = 3414 Btu/h, equation (2.7) is converted to
(2.8)
Equation (2.8) can be generally applied to different scenarios for power supply such as power import, on-site power generation from back pressure and condensing steam turbines as well as from gas turbines, which are discussed in detail in Chapter 3.
2.3.4 Energy Intensity Based on FE
By converting different energy forms to their fuel equivalent, process energy intensity in equation (2.3) can be revised to give
(2.9)
where FE is the total fuel equivalent as a summation of individual fuel equivalent for different energy forms across the process battery limit.
2.4 Energy Intensity for a Total Site
The structure of energy intensity indicators can be organized in a hierarchal manner. That is, intensity indicators are developed for processes first and toward a total site. One may question why the concept of energy intensity does not apply to process sections (e.g., reaction section, product fractionation section) of a process. The reason is that there is strong heat integration between sections of a process unit, and thus energy intensity for sections cannot fairly represent section energy performance. Energy transfer across process units could occur, but the chance is much slim compared with between-process sections. In case of heat transfer between processes, some adjustment must be made to account for it.
To calculate the energy intensity index for the whole site, aggregate energy intensity could be defined simply as the ratio of total energy in fuel equivalent divided by total activity:
(2.10)
where FEi is the total fuel equivalent for process i.
However, there is a problem here with this simple aggregate approach: Although energy in fuel equivalent is additive, feeds (F) are not because processes usually have different feeds with very different compositions. In other words, the problem with equation (2.10) is the dissimilarity in feeds, which cannot be added without treatment.
To overcome this dissimilarity problem in feeds, we could think of a reference site with energy intensity for each process known in prior. Thus, the total amount of energy use could be calculated for the reference site, as the summation of the energy intensity for the reference processes. Let us derive the mathematical expressions along this line of thought.
When the energy intensity for a reference process is known or can be calculated, applying equation (2.9) gives the energy use for a reference process as
(2.11)
Since FE is additive, the total energy use for the reference site is
(2.12)
Then, an intensity index for the site of interest can be defined as the ratio of actual and reference energy use:
(2.13)
FEsite,actual can be readily calculated from individual energy users consisting of fuel, power, steam, BFW and cooling water accross the site battery limit.
You may ask a critical question: A real process could differ from the reference process in terms of feed rates and process conditions. How can we deal with these differences in the energy intensity index calculations? This question can be addressed by defining the intensity as a function of three major factors:
(2.14)
where design, conditions, and weather reflect the actual process. In this way, equation (2.14) describes the energy performance for the reference processes with the same attributes as the actual processes, but the energy intensity could be different. This is because the energy intensity in equation (2.14) for reference processes is developed based on peers' performance, while the energy intensity for actual processes is calculated based on real data.
The simplest form is a linear expression. For example, if two operating parameters are considered, the linear form becomes
(2.15)
where a is a structural term that reflects the design performance, while b and c are the sensitivity factors for x1 (process condition 1) and x2 (process condition 2), respectively; d is the correction factor for weather; and Tambient is the ambient temperature in local area.
2.5 Concluding Remarks
The decline in energy intensity is a proxy for efficiency improvement; however, energy intensity reflects production and hence is much more universal and communicable across the process industry.
Clearly, structural and operational changes for efficiency improvements in processes and equipment can contribute to reduction in process energy intensity in a big way. A state-of-the-art process gives low energy intensity by design. However, it could end up with high operating energy intensity if the process is poorly operated. On the other hand, a poorly designed process could achieve its best potential if it is operated with diligence. However, good operation could reach the design limit because the performance is handicapped due to inherently inefficient design. To improve the process beyond this design limitation, structural changes must be made.
Nomenclature
Aactivity such as processing feed or making productsEenergy useFfeed rateFEfuel equivalent; amount of fuel at the source to make a unit of energy utility (power, steam)Genergy utilityIenergy intensity; energy units/feed or product unitQheat contentTtemperatureGreek Letters
ηcyclepower generation efficiency; the ratio of the amount of fuel to make a unit of powerSubscript
refreference process or total siteReferences
Schipper L, Howarth RB, Carlassare E (1992a) Energy intensity, sector activity, and structural changes in the Norwegian economy, Energy: The International Journal, 17, 215–233.
Schipper L, Meyers S, Howarth RB, Steiner RL (1992b) Energy Efficiency and Human Activity: Past Trends, Future Prospects, pp. 250–285, Cambridge University Press, Cambridge.
3
Benchmarking Energy Intensity
Energy benchmarking defines an intensity measure of process energy performance. It can be used to determine the baseline of energy performance to compare with peers and measure the effects by operation and process changes.
3.1 Introduction
When you are given a task to improve energy performance for the total site or process unit, your immediate response would be: Where should I start? The answer is to know where the process unit stands in energy performance. In other words, you need to determine both the current energy use and energy consumption target. Only then is it possible to establish the baseline and to know how well the process unit is doing by comparing current performance against the target. We call the exercise of establishing a baseline as energy benchmarking.
The most important result of energy benchmarking is the indication of energy intensity for individual processes. If a performance target can be defined based on a corporate target, industrial peer performance, or the best technology performance for each process, then the benchmarking audit can determine the process energy performance overall in comparison with targeted performance. In general, benchmarking assessment can determine several scenarios:
The Need of Having an Overall Energy Optimization Effort: If large gaps are available for majority of the process units, this could imply that there are many opportunities available and require consorted effort across the site. A dedicated energy team may need to be established to coordinate the overall effort in identifying and capturing the opportunities.Areas for Focus: Some of the process units are identified with large performance gaps and these processes can be selected as focus areas. This allows us to effectively concentrate efforts on areas with the greatest potential for improvement. Specialists may need to be assembled to form a project team.Update Targets: If all major process units are under good performance relative to the targets, the plant may concentrate its efforts on continuous improvements via setting more aggressive targets.3.2 Data Extraction from Historian
For the purpose of energy benchmarking of a process unit, the important thing is to identify the main energy consumers and give a reasonable estimate for missing data. Going overboard to collect miniature details and chase utmost precision should be avoided at this stage. Doing so may actually waste effort because such fine details are most likely not needed in the benchmarking calculations and will not make a reasonable impact on energy optimization.
Table 3.1 gives an example on the relevant data needed for energy benchmarking. Although all the data look familiar in the table, you may question the need for including the fuel generated in the unit as part of energy generation. As a general guideline, the fuel produced by a process unit, in the forms of fuel gas, LPG, and fuel oil, is treated as part of products from the process and thus should not be included in the energy balance for the unit.
Table 3.1 Example Data Set for Energy Use and Generation.
To have a clear view of energy flows into and out of the process, we derive Figure 3.1 based on data in Table 3.1. The left-hand side of the figure shows the energy input to the process. At the same time, exothermic reaction provides additional heat to the process. On the right-hand side of the figure, energy leaves the process, which includes heat exported and lost. In addition, the raw feed and boiler feed water (BFW) carry a certain amount of energy into the process based on an assumed reference temperature of 100 °F. A different reference temperature could be used and fuel equivalent calculations should be conducted based on the chosen reference temperature. A reference temperature is selected based on the consideration that any heat below the reference temperature is not economically viable to recover.
Figure 3.1 Energy flows into and out of the process unit.
3.3 Convert All Energy Usage to Fuel Equivalent
In the industry, steam is measured in mass flow, fuel in volumetric flow, and electricity in electrical current. To compare them on the same basis, all the energy use and generation need to be traced back to fuel fired at the source of energy generation to obtain the fuel equivalent (FE), which is a cardinal rule for energy balance calculations. The following illustrates how to conduct FE calculations based on Figure 3.1.
Assumptions: First, assumptions for related fuel equivalent factors need to be made and the basis for deriving these assumptions will be explained later. Assumed FE factors are as follows:
FE for purchased power = 9.09 MMBtu/MWhFE for high-pressure (HP) steam = 1550 Btu/lbFE for medium-pressure (MP) steam = 1310 Btu/lbFE for condensate = 94.6 Btu/lbFE for BFW @250 °F = 177 Btu/lbConvert Energy Inputs and Outputs to Fuel Equivalent:
FE for power = 3.15 MW × 9.09 MMBtu/MWh = 28.6 MMBtu/hFE for HP steam = 188.6 klb/h × 1.55 MMBtu/klb = 292.3 MMBtu/hFE for fuel fired = 337.1 MMBtu/hFE for MP steam export = 50 klb/h × 1.31 MMBtu/klb = 65.5 MMBtu/hFE for Condensate return = 129.4 klb/h × 94.6 Btu/lb × 103 lb/klb × 1 MMBtu/106 Btu = 12.2 MMBtu/hFE for Condensate loss = 10 klb/h × 94.6 Btu/lb × 103 lb/klb × 1 MMBtu/106 Btu = 0.9 MMBtu/hTo reveal the significance of FE calculations, let us assume a process receives 20 klb/h of HP steam in which 10 klb/h comes from a boiler with efficiency of 75% and another 10 klb/h from a boiler with efficiency of 85%. Obviously, the fuel required or fuel equivalent for the same amount of HP steam, that is, 10 klb/h, by the two boilers is very different: The fuel equivalent from the boiler with 85% efficiency is 15.35 MMBtu/h, resulting in FE factor of 1.535 MMBtu/klb. The fuel equivalent for the boiler with 75% efficiency is 16.38 MMBtu/h giving the FE factor of 1.638 MMBtu/klb. We can think of another example of power generation on site by a combined cycle (gas and steam turbines) cogeneration facility versus a coal-fired steam turbine power plant. The fuel equivalent for the same amount of power from these two sources can be very different. Therefore, we cannot overstate the importance for tracing any energy back to fuel equivalent.
3.4 Energy Balance
After converting all energy forms to fuel equivalent, these energy forms are leveled on the equal basis and thus we are ready to conduct energy balance. For a chemical process, energy balance is defined as
(3.1)
The sum of energy supply and energy generation (heat of reaction) makes total energy input, while both energy export and energy loss forms total energy output. Energy supply implies the energy coming into the process battery limit. Energy generation for a chemical process implies heat of reaction. If a reaction is exothermic, the term of energy generation takes a positive sign because it contributes to total energy input. An endothermic reaction takes a negative sign because it takes energy away from energy supply and needs energy input to make up the difference. Energy export denotes the energy leaving out of the process that is used by other processes. Energy loss indicates the energy flows leaving out of the process but lost to the environment.
After obtaining fuel equivalent values for all energy flows, we can convert Figure 3.1 to Figure 3.2, which gives a visualized energy balance around the process unit including energy supply, energy generation by heat of reaction, and energy export and losses. The heat of exothermic reaction is calculated as 141 MMBtu/h for this example based on the feed composition and reaction conditions. Heat content of the feed and boiler feed water above 100 °F are treated as energy input. At the same time, the figure shows energy output including energy export and energy losses. It can be observed that only energy flows entering and leaving the process battery limit are addressed in the energy balance described in Figure 3.2.
Figure 3.2 Energy balance in a visualized form.
The detailed energy balance is given in Table 3.2. The total energy input is 819.2 MMBtu/h for the process unit currently operated. The heat of exothermic reaction contributes positively to the total energy input. Fuel fired in process heaters is 337.1 MMBtu/h, which is the most dominant accounting for about 40% of total energy input. The second most dominant energy use is the process shaftwork demand. HP steam of 292.3 MMBtu/h is used for steam turbines as process drivers, while purchased electricity of 28.6 MMBtu/h is for running motors. The total fuel equivalent for meeting the process shaftwork demand is 321 MMBtu/h (28.6 + 292.3), which accounts for another 40% of total energy input. Heat of reaction contributes a significant portion of the energy input at 17%. The remaining minor contributions to the energy input come from feed and boiler feed water.
Table 3.2 Tabulated Energy Balance for the Example.
Energy output is grouped into two categories, namely, energy export and energy losses. Energy export includes any energy flow going out of the process and being used for a meaningful purpose. In the example, the energy export is 77.7 MMBtu/h, which includes MP steam to the steam header and condensate return to the boilers. It could also include hot products directly sent to downstream processes as feeds, which is not present in this example.
Energy losses are mainly caused by process water and air cooling. To derive the fuel equivalent, a process cooling duty is divided by the boiler efficiency (85% for this example) assuming low-temperature heat available in process cooling could be used for boiler feed water preheating. Total cooling duty accounts for 68% of total energy losses. Therefore, one critical area for improving process energy efficiency is to identify opportunities to reduce heat losses in process cooling although the heat is usually available at low temperatures.
Fuel equivalent for purchased power is assumed to be 9090 Btu/kWh compared with the normal conversation factor of 3414 Btu/kWh. This assumption implies power generation loss of 5676 (= 9090 − 3414) Btu for each kWh imported. Thus, power generation loss is 17.9 MMBtu/h for 3.15 purchased. The rationale for this assumption will be discussed later with the FE calculation given in equation (3.7).
Furnace stack loss is calculated based on actual heater efficiency. For this example, 55% furnace efficiency is assumed for the charge heater and the diesel stripper heater, which have a radiant section only. A furnace efficiency of 85% is used for the product fractionator heater and the debutanizer reboiler heater, which have both radiant and convection sections.
The mechanical losses for pumps and motors are calculated based on motor efficiency, which is assumed at 90% for this example.
The net energy input is expressed as
(3.2)
For the example in question, net energy input = 819.2 − 77.7 = 741.5 MMBtu/h.
Let us define specific energy use the same as the energy intensity:
(3.3)
Applying equation (3.3) yields
Specific energy = 741.5 MMBtu/h × 1000 kBtu/MMBtu/37,000 bbl/day ×24 h/day = 480.9 kBtu/bbl, where 37,000 bbl/day is the process feed rate.
As manifested in Chapter 2, specific energy use is a very insightful concept as it represents the energy intensity of production indicated by the amount of energy required for processing one unit of feed.
3.5 Fuel Equivalent for Steam and Power
In previous discussions, some assumptions of fuel equivalent factors were made for power and steam. You may ask: What is the basis for making these assumptions? How do you determine fuel equivalent values for power and steam in your plant? Let us consider the calculation of fuel equivalent for power first.
3.5.1 FE Factors for Power (FEpower)
As mentioned in Chapter 2, FEpower is expressed as
(3.4)
where ηcycle is the cycle efficiency of power generation and thus ηcycle = Qpower/Qfuel with Qpower (in Btu/h) representing the amount of heat content associated with power with a conversion factor of 3414 Btu/kWh.
By using the conversion factor of 1 kW = 3414 Btu/h, equation (3.4) can be converted to
(3.5)
Rearranging equation (3.5) leads to
(3.6)
where W = (Qpower/3414) and W (in kW) represents the amount of power. By converting the unit of FEpower from Btu/Btu in equation (3.4) to Btu/kWh in equation (3.6), the expression of FEpower in equation (3.6) becomes exactly the same as that of heat rate for power generation. Let us look at three cases for applying equation (3.6).
Case 1: Importing Power from Coal Power Plants
The average efficiency for today's coal-fired plants is 33% globally, while pulverized coal combustion can reach efficiency of 45% based on net low heating value (LHV) (IEA, 2012). Thus, the fuel equivalent factor for purchased coal power are in the range of 7.58 MMBtu/MW (45% of power efficiency) and 10.34 MMBtu/MW (33%). For example, if assuming steam cycle efficiency is 37.56%, applying equation (3.5) yields
(3.7)
Note that 9090 Btu/kWh is the FEpower factor used in the previous assumption for power.
Case 2: On-Site Power Generation from Steam Turbines
For on-site power generation, usually heat rate is known and it should be used as FEpower. If unknown, a typical condensing steam turbine cycle efficiency of 30% could be used to yield
(3.8)
FEpower factors for back pressure steam turbines could be much higher than 11,380 Btu/kWh. What is the interpretation of a higher FEpower from on-site power generation than that of purchased power? The implication is that a commercial power plant can make power more efficiently than a process plant if cogeneration is not involved. Does it mean that the use of a motor is more energy efficient than using an on-site condensing turbine for process drivers? The answer is Yes. You may stretch out to think: The back pressure turbines could be even worse as process drivers. Is this true? The answer for this question relies on the steam balances. If the exhaust steam from the back pressure turbines is used for processes, the back pressure turbines have much higher cogeneration efficiency (power plus steam).
Case 3: On-Site Power Generation from Combined Gas and Steam Turbines
When power is generated by a gas turbine (GT), gas turbine exhaust is usually sent to the heat recovery steam generator for steam generation. Steam is then used for further power generation via steam turbines. A configuration such as this is known as a gas turbine–steam combined cycle.
The combined cycle efficiency can be expressed as
(3.9)
By applying equation (3.5), the fuel equivalent factor for power generated from a combined cycle would be
(3.10)
