Wiley-ASME Press Series List
Combined Cooling, Heating, and Power Systems: Modeling, Optimization, and Operation | Shi | August 2017 |
Applications of Mathematical Heat Transfer and Fluid Flow Models in Engineering and Medicine | Dorfman | February 2017 |
Bioprocessing Piping and Equipment Design: A Companion Guide for the ASME BPE Standard | Huitt | December 2016 |
Nonlinear Regression Modeling for Engineering Applications | Rhinehart | September 2016 |
Fundamentals of Mechanical Vibrations | Cai | May 2016 |
Introduction to Dynamics and Control of Mechanical Engineering Systems | To | March 2016 |
This edition first published 2017
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Library of Congress Cataloging-in-Publication Data
Names: Shi, Yang, 1972- author. | Liu, Mingxi, 1988- author. | Fang, Fang, 1976- author.
Title: Combined cooling, heating, and power systems : modeling, optimization, and operation / Yang Shi, Mingxi Liu, Fang Fang.
Description: Singapore ; Hoboken, NJ : John Wiley & Sons, 2017. | Includes bibliographical references and index. | Description based on print version record and CIP data provided by publisher; resource not viewed.
Identifiers: LCCN 2017004053 (print) | LCCN 2017012538 (ebook) | ISBN 9781119283379 (Adobe PDF) | ISBN 9781119283423 (ePub) | ISBN 9781119283355 (cloth)
Subjects: LCSH: Cogeneration of electric power and heat. | Cooling systems. | Heating.
Classification: LCC TK1041 (ebook) | LCC TK1041 .S55 2017 (print) | DDC 621.1/99-dc23
LC record available at https://lccn.loc.gov/2017004053
Cover image: © artJazz/Gettyimages
Cover design by Wiley
To my beloved parents and family
–Yang Shi
To my beloved parents and Jingwen
–Mingxi Liu
To my beloved parents and family
–Fang Fang
The Wiley-ASME Press Series in Mechanical Engineering brings together two established leaders in mechanical engineering publishing to deliver high-quality, peer-reviewed books covering topics of current interest to engineers and researchers worldwide. The series publishes across the breadth of mechanical engineering, comprising research, design and development, and manufacturing. It includes monographs, references and course texts.
Prospective topics include emerging and advanced technologies in Engineering Design; Computer-Aided Design; Energy Conversion & Resources; Heat Transfer; Manufacturing & Processing; Systems & Devices; Renewable Energy; Robotics; and Biotechnology.
Combined cooling, heating and power (CCHP) is a feature of trigeneration systems able to supply cooling, heating, and electricity simultaneously. CCHP systems can be employed to provide buildings with cooling, heating, electricity, hot water and other uses of thermal energy. CCHP features with the great potential of dramatically increasing resource energy efficiency and reducing carbon dioxide emissions. Our intention through this book is to provide a timely account as well as an introductory exposure to the main developments in modeling, optimization, and operation of CCHP systems. At the time of conceiving this project, we believed that the development of a systematic framework on modeling and optimal operation design of CCHP systems was of paramount importance. A concise overview of the research area is presented in Chapter 1. We hope it will help readers arrive at a broader and more balanced view of CCHP systems. The remainder of the book presents the core contents, which are divided into five chapters. In Chapter 2, based on two conventional operation strategies, that is, following electric load (FEL) and following thermal load (FTL), a novel optimal switching operation strategy is presented. Chapter 3 presents a configuration with hybrid chillers and design of the optimal operation strategy. In Chapter 4, based on the concept of energy hub, a system matrix-based model is proposed to systematically facilitate the design of optimal operation strategies. Chapter 5 discusses the load prediction problem which plays an instrumental role in designing CCHP operation schemes. In Chapter 6, a complementary CCHP-organic Rankine cycle (CCHP-ORC) system is introduced.
The writing of this monograph has benefitted greatly from discussions with many colleagues. We wish to express our heartfelt gratitude to Professor Jizhen Liu who shared many of his ideas and visions with us. Others who contributed directly by means of joint research on the subject include Le Wei, Qinghua Wang, Hui Zhang, and Huiping Li, with whom we have enjoyed many collaborations. We have also benefitted from constructive and enlightening discussions with Jianhua Zhang, Guolian Hou, Jian Wu, Ji Huang, Xiaotao Liu, Chao Shen, Yuanye Chen, Bingxian Mu, Jicheng Chen, and Kunwu Zhang, among others. Support from the Natural Sciences and Engineering Research Council of Canada, from the National Natural Science Foundation of China (under grant 61473116 and 51676068) has been very helpful and is gratefully acknowledged. Finally, as a way of expressing our deep gratitude and indebtedness, the first author dedicates this book to his wife Jing, and Eric and Adam, the second author to his wife Jingwen, and the third author to his wife Le, and Bowen and Yihe, for their great support and encouragement on this project.
Yang Shi, Mingxi Liu, Fang Fang
Victoria, BC, Canada
The authors would like to thank all those who have helped in accomplishing this book.
AFC | Alkaline Fuel Cell |
ANN | Artificial Neural Network |
AR | AutoRegressive |
ARIMA | AutoRegressive Integrated Moving Average |
ARMA | AutoRegressive Moving Average |
ARMAX | AutoRegressive Moving Average with eXogenous inputs |
ATC | Annual Total Cost |
ATCS | Annual Total Cost Saving |
ATD | Aggregate Thermal Demand |
BFGS | Broyden–Fletcher–Goldfarb–Shanno |
CCHP | Combined Cooling, Heating, and Power |
CDE | Carbon Dioxide Emissions |
CDER | Carbon Dioxide Emissions Reductions |
CHP | Combined Heating and Power |
CITHR | Cooling-side Incremental Trigeneration Heat Rate |
COP | Coefficient of Performance |
DHC | District Heating and Cooling |
DOE | Department of Energy |
EA | Evolutionary-Algorithmic |
EBMUD | East Bay Municipal Utility District |
EC | Evaluation Criteria |
EDM | Electric Demand Management |
EITHR | Electrical-side Incremental Trigeneration Heat Rate |
EPA | Environmental Protection Agency |
EUETS | European Union Emissions Trading Scheme |
ec | Electric Chiller |
FCL | Following Constant Load |
FEL | Following the Electric Load |
FTL | Following the Thermal Load |
GA | Genetic Algorithm |
GHG | GreenHouse Gas |
GRG | Generalized Reduced Gradient |
GRU | Gainsville Regional Utilities |
HETL | Hybrid Electric-Thermal Load |
hrc | Recovered Heat for Cooling |
hrh | Recovered Heat for Heating |
HRSG | Heat Recovery Steam Generator |
hrs | Heat Recovery System |
HTC | Hourly Total Cost |
HTCS | Hourly Total Cost Savings |
HVAC | Heating, Ventilation, and Air Conditioning |
IC | Internal Combustion |
IV | Instrument Variable |
KKT | Karush–Kuhn–Tucker |
LP | Linear Programming |
LS | Least Squares |
MA | Moving Average |
MAE | Mean Absolute Error |
MAFC | Magnesium-Air Fuel Cell |
MAPE | Mean Absolute Percentage Error |
MCFC | Molten Carbonate Fuel Cell |
MILP | Mixed Integer Linear Programming |
MINLP | Mixed Integer Non-Linear Programming |
MSPE | Mean Square Prediction Error |
MPC | Model Predictive Control |
OLS | Ordinary Least Squares |
ORC | Organic Rankine Cycle |
PAFC | Phosphoric Acid Fuel Cell |
PEMFC | Proton Exchange Membrane Fuel Cell |
PEC | Primary Energy Consumption |
PES | Primary Energy Savings |
PGU | Power Generation Unit |
PURPA | Public Utility Regulatory Policy Act |
PV | PhotoVoltaic |
QP | Quadratic Programming |
SNPV | System Net Present Value |
SOFC | Solid Oxide Fuel Cell |
SP | Separation Production |
SQP | Sequential Quadratic Programming |
TDM | Thermal Demand Management |
TITHR | Thermal-side Incremental Trigeneration Heat Rate |
TPES | Trigeneration Primary Energy Saving |
TRR | Total Revenue Requirement |
TSLS | Two-Stage Least Squares |
TSRLS | Two-Stage Recursive Least Squares |
WADE | World Alliance for Decentralized Energy |
The th equality constraint of variable | |
ATC | Annual total cost |
ATCS | Annual total cost savings |
Unit price of the absorption chiller | |
Unit price of the boiler | |
Carbon tax rate | |
Electricity rate | |
Unit price of the electric chiller | |
Natural gas rate | |
Unit price of the heating unit | |
The th inequality constraint of variable | |
Unit price of the PGU | |
Electricity sold-back rates | |
CDE | Carbon dioxide emissions |
Carbon dioxide emissions of the CCHP system | |
Carbon dioxide emissions of the CCHP system under FEL | |
Carbon dioxide emissions of the CCHP system under FTL | |
Carbon dioxide emissions of the SP system | |
CDER | Carbon dioxide emissions reductions |
Coefficient of performance of the absorption chiller | |
Coefficient of performance of the electric chiller | |
COST | Operational cost |
Operational cost of the CCHP system under FEL | |
Operational cost of the CCHP system under FTL | |
Operational cost of the SP system | |
Covariance of variables • and | |
Expectation of variable | |
Electricity consumed by the electric chiller in the CCHP system | |
Electricity consumed by the electric chiller in the SP system | |
Excess electricity | |
Purchased electricity from the grid by the CCHP system | |
Purchased electricity for compensating for the cooling gap | |
Purchased electricity from the grid by the SP system | |
Standard basis vector with the th element being 1 | |
Electricity input of component | |
Electricity output of component | |
Maximum electricity generated by the PGU | |
Electricity output of the ORC | |
Parasitic electricity | |
Electricity generated from the PGU | |
Maximum electricity generated by the PGU | |
Electricity generated from the PGU under FEL | |
Electricity generated from the PGU under FTL | |
Electricity generated by the PGU | |
Electricity required by building users and the electric chiller | |
Electricity required by building users | |
Lower bound of electricity required by building users | |
Upper bound of electricity required by building users | |
EC | Evaluation criteria function value |
Annual evaluation criteria function value | |
Evaluation criteria function value of the CCHP system under FEL | |
Evaluation criteria function value of the CCHP system under FTL | |
Hourly evaluation criteria function value | |
Hourly evaluation criteria function value of day , hour | |
Fuel consumed by the boiler in the CCHP system | |
Fuel consumed by the boiler in the SP system | |
Fuel consumed by the boiler in the CCHP system under FEL | |
Fuel consumed by the boiler in the CCHP system under FTL | |
Fuel consumed by the CCHP system | |
Fuel input ofcomponent | |
Total fuel consumption | |
Additionally purchased fuel | |
Total fuel consumption of the CCHP system under FEL | |
Total fuel consumption of the CCHP system under FTL | |
Fuel output of component | |
Fuel consumed by the PGU | |
Fuel consumed by the PGU in the CCHP system under FEL | |
Fuel consumed by the PGU in the CCHP system under FTL | |
Maximum fuel consumption of the PGU | |
Optimal PGU capacity | |
Reduced fuel consumption | |
Fuel consumed by the SP system | |
Energy conversion matrix of component | |
Enthalpy of organic fluid at the inlet of pump | |
Enthalpy of organic fluid at the outlet of pump | |
Enthalpy at the outlet of pump for the isentropic case | |
Enthalpy of organic fluid at the outlet of the evaporator | |
Enthalpy of organic fluid at the outlet of the pump | |
Enthalpy of organic fluid at the outlet of the turbine for the isentropic case | |
HTC | Hourly total cost |
Hourly total cost of the CCHP system | |
Hourly total cost of the SP system | |
HTCS | Hourly total cost savings |
K | Power to heat ratio |
Site-to-primary energy conversion factor for electricity | |
Site-to-primary energy conversion factor for natural gas | |
L | Facility's life |
Maximize the function value of | |
Minimize the function value of | |
Maximum value between • and | |
Minimum value between • and | |
Organic fluid mass flow rate | |
PEC | Primary energy consumption |
Primary energy consumption of the CCHP system | |
Primary energy consumption of the CCHP system under FEL | |
Primary energy consumption of the CCHP system under FTL | |
Primary energy consumption of the SP system | |
PES | Primary energy savings |
Cooling energy provided by the absorption chiller | |
Total cooling demand | |
Heat exchange of the condenser | |
Cooling energy provided by the electric chiller | |
Obtained heat by evaporator | |
Equivalent total thermal requirement at the output of the heat recovery system | |
Thermal energy provided by the boiler in the CCHP system | |
Thermal energy provided by the boiler in the SP system | |
Thermal energy gap | |
Total heating demand | |
Heating input of component | |
Heating output of component | |
Thermal energy from the heat recovery system for the use of cooling | |
Thermal energy from the heat recovery system for the use of heating | |
Thermal energy provided by the PGU | |
Thermal energy provided by the heat recovery system | |
Thermal energy required by building users and the electric chiller | |
Thermal energy provided by the heat recovery system under FEL | |
Thermal energy provided by the heat recovery system under FTL | |
Thermal input of the ORC | |
Total thermal demand by building users | |
R | Capital recovery factor |
Dew-point temperature | |
Observation of the dew-point temperature | |
Dry-bulb temperature | |
Observation of the dry-bulb temperature | |
Estimation of the dry-bulb temperature | |
Energy input vector of component | |
Energy output vector of component | |
Forecasted load vector | |
Upper bound of the output of component | |
Lower bound of the output of component | |
Variance of variable | |
Pump power | |
x | Electric cooling to cool load ratio |
Variable of cooling load | |
Variable of forecasted cooling load | |
Variable of remained cooling to be provided | |
Variable of electric load | |
Variable of forecasted electric load | |
Variable of heating load | |
Variable of forecasted heating load | |
Variable of remained heating to be provided | |
time lags from the current time instant | |
Dispatch matrix of component | |
Efficiency of the heating unit | |
Efficiency of the PGU | |
Efficiency of the heat recovery system | |
Efficiency of the boiler | |
Generation efficiency of the SP system | |
Transmission efficiency of local grid | |
Isentropic efficiency | |
Efficiency of the ORC | |
Efficiency of the electric generator | |
Carbon dioxide emissions conversion factor of electricity | |
Carbon dioxide emissions conversion factor of natural gas | |
Evaporator effectiveness | |
Weighting coefficient of the th criterion | |
Gradient | |
Centigrade | |
Exists | |
In | |
Define | |
Sum | |
For all | |
Subject to | |
Matrix/vector transpose | |
Real vector space of dimension | |
Real matrix space of dimension | |
The optimal value of variable • | |
O | Complexity |
Combined cooling, heating, and power (CCHP) systems are known as trigeneration systems. They are designed to supply cooling, heating, and electricity simultaneously. The CCHP system has become a hot topic for its high system efficiency, high economic efficiency, and low greenhouse gas (GHG) emissions in recent years. The efficiency of the CCHP system depends on the appropriate system configuration, operation strategy, and facility selection. Due to the inherent and inevitable energy waste of traditional operation strategies, high-efficiency operation strategies are urged. To achieve the highest system efficiency, facilities in the system should be appropriately sized to match with the corresponding operation strategy.
In Chapter 1, the state-of-the-art of CCHP research is surveyed. First, the development and working scheme of the CCHP system is presented. Some analyses of the advantages of this system and a brief introduction to the related components are then given. In the second part of Chapter 1, we elaborately introduce various types of prime movers and thermally activated facilities. Recent research progress on the management, control, system optimization, and facility selection is summarized in the third part. The development of the CCHP system in representative countries and the development barriers are also discussed in Chapter 1.
The operation strategy has a direct impact on the CCHP system performance. To improve the operational performance, in Chapter 2, based on two conventional operation strategies, that is, following electric load (FEL) and following thermal load (FTL), a novel optimal switching operation strategy is proposed. Using this strategy, the whole operating space of the CCHP system is divided into several regions by one to three border surfaces determined by energy requirements and the evaluation criteria (EC). Then the operating point of the CCHP system is located in a corresponding operating mode region to achieve improved EC. The EC simultaneously considers the primary energy consumption, the operational cost, and the carbon dioxide emissions. The proposed strategy can reflect and balance the influences of energy requirements, energy prices, and emissions effectively.
Most of the improved operation strategies in the literature are based on the “balance” plane, matching of the electric demands with the thermal demands. However, in more than 95% energy demand patterns, the demands cannot match with each other on this exact “balance” plane. To continuously use the “balance” concept, in Chapter 3, the system configuration is modified from the one with a single absorption chiller to be the one with hybrid chillers, thus expanding the “balance” plane to a “balance” space by tuning the electric cooling to cool load ratio. With this new “balance” space, an operation strategy is designed and the power generation unit (PGU) capacity is optimized according to the proposed operation strategy to reduce the energy waste and improve the system efficiency. A case study is conducted to verify the feasibility and effectiveness of the proposed operation strategy.
In Chapter 4, a more mathematical approach to scheduling the energy input and power flow is proposed. By using the concept of energy hub, the CCHP system is modeled in a matrix form. As a result, the whole CCHP system is an input–output model. Setting the objective function to be a weighted summation of primary energy savings (PES), hourly total cost savings (HTC), and carbon dioxide emissions reductions (CDER), the optimization problem, constrained by equality and inequality constraints, is solved to obtain the optimal operation strategy. The PGU capacity is also sized under the proposed optimal operation strategy. In the case study, compared with FEL and FTL, the proposed optimal operation strategy saves more primary energy and annual total cost, and can be more environmentally friendly.
Chapter 5
The electricity to thermal energy output ratio is an important impact factor for the operation strategy and performance of CCHP systems. If the energy requirements of users are managed to just match this ratio, the system efficiency would reach the maximum. However, due to the randomness of users' demand, this situation is rarely achieved in practice. To solve this problem, a complementary CCHP-organic Rankine cycle (CCHP-ORC) system is configured in Chapter 6. The salient feature of this system is that its electricity to thermal energy output ratio can be adjusted by changing the loads of the electric chiller and the ORC dynamically. For such a system, an optimal operation strategy and a corresponding implemented decision-making process are presented within a wide load range. Case studies are conducted to verify the efficacy of the developed CCHP-ORC system.