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Heuristic methods for the evaluation of environmental impacts Chapter | 12 317

Second [45], the cost per ton of emissions of CO 2 has varied between 9
and 24 euros. These authors as mentioned earlier also make an equivalence
between the tons of other pollutants and tons of CO 2 . Considering the above
criteria, you can calculate the cost using the emission index by the following
approximation:
Cost emissions 5 24 3 I em in euros ð12:8Þ

12.3 A mathematical model for the optimization of EED
considering the emission index

Optimizing the EED is one of the most important tasks in power plants with
internal combustion engines. The ED energy with a single goal cost of fuel
only considers the one objective, that is, the question of generation. It has
given way to multiobjective orders because of the environmental issues that
arise from emissions from thermal plants. The purpose of this chapter is to
analyze a new solution optimizing the EED by the technique of NSGA-II but
using the new concept of emission index instead of using emissions as a cost
or as much of greenhouse gases.
The EED of the problem is to minimize the total cost of generation and
emission levels while at the same time to satisfy the demand of generation
plants.
Thermal power generation is one of the sources of significant carbon
dioxide (CO 2 ), sulfur dioxide (SO 2 ), and nitrogen oxides (NO x ) that create
air pollution [13]. The classic problem generating ED is to provide the
required amount of power at the lowest cost, to meet the demand and opera-
tional restrictions.
This is a very complex problem to be solved for its high dimensionality,
a nonlinear objective function, and many restrictions. Various techniques,
such as Integer Programming [46], Dynamic Programming [47], Newton’s
method for [48], and the functions of Lagrange by [49], have been used to
solve the problem EED generation.
To solve the EED problem, other optimization methods, such as the
method of simulated annealing (simulated annealing goal attainment) pointed
to by [50], particle swarm used by [51], the Game Theory used by [52], and
the approach using the technique for order preference by a similarity of the
ideal solution (TOPSIS) [53].
Various methods have also been developed on the basis of mathematical
approaches to offer a quicker solution to the ED [54]. EAs have also been
applied to the ED of the problem in question [55]. The research has also
been developed to minimize the costs, including emission restrictions to
solve the ED of generation and selection of generators [56]. Recently, it has
been successfully employed by a combination of gravitational search