Page 31 - Sustainability in the process industry

8 Cha p te r O n e

energy sources such as biomass, solar photovoltaic (PV), and solar
thermal into the combined heating and cooling cycles. Since 1995, the
energy consumption of European Community (EC) member countries
has risen by 11 percent to the equivalent of 1637 Mt (megatons) of oil
equivalent (Eurostat, 2007). This increase in energy consumption
contrasts with the trend of the EC population, which is growing at
only about 0.4 percent annually (Eurostat, 2007). The overall share of
total energy consumption by industry is declining in most countries.
However, domestic energy consumption is rising. In the United
Kingdom, for example, residential consumption rose from 35.6 Mt
(oil equivalent) in 1971 to 48.5 Mt in 2001—an increase of 36 percent—
despite increases in energy efficiency (DTI, 2006).
Process Integration Technology (Pinch Technology) has been
extensively used in the processing and power generating industry
for more than 30 years. It was pioneered by the Department of Process
Integration, UMIST (now the Centre for Process Integration, CEAS,
the University of Manchester), in the late 1980s and 1990s. Heat
Integration is introduced in Chapter 2 and is described in more detail
in Chapter 4. Water and mass integration is covered in Chapter 5, and
recent developments in the field are reviewed in Chapter 6.

1.6 Optimal Process Synthesis and
Combinatorial Graphs
Process synthesis is a complex engineering activity that involves
process modeling (e.g., chemical engineering) as well as combinatorial
challenges. Although the basic process modeling has reached a
considerable level of maturity, the combinatorial aspects of the
engineering problem still leave significant room for improvement.
One innovative approach to process synthesis is to exploit the
combinatorial nature of network optimization. This approach is used
by the process-graph (P-graph) framework, which explicitly defines
sets of process materials and operations and then uses efficient
combinatorial algorithms to build a rigorous network superstructure
that can be reduced to the optimal network topology. This is different
from the Mathematical Programming (MPR) approach, where the
combinatorial aspects are modeled by algebraic equations and the
structural features are blended with the underlying process models.
These approaches are covered in Chapters 3, 7, and 8.
The P-graph framework has been successfully applied to and
demonstrated on several cases of energy system design. For example,
Varbanov and Friedler (2008) explored FC-based systems in a case
study that evaluated energy conversion systems to reduce CO
2
emissions via Fuel-Cell Combined Cycle (FCCC) subsystems that
utilize biomass and/or fossil fuels. The combinatorial complexity of
the problem is efficiently handled by using P-graph framework and