Civil Engineering Reference
In-Depth Information
to hot water preparation, 12 % to lighting and 15 % to other needs. In Lithuania,
however, the share of heating amounts to as many as 47 % of all energy consumed.
Hence, when we consider such consumer group as households, any measure that
helps conserve energy resources and choose the most efficient solutions is
important. Households may conserve energy in two ways, which are innovative
products and technological solutions, and changed behaviours. The prices of
natural resources are growing, people are realizing the scale of environmental
issues, and renewable energy generation technologies are advancing; these are the
reasons why ever more households adopt advanced energy supply systems based
on renewable resources.
To formulate a real-life multiple-criteria analysis problem, energy generation
technologies employing different primary and traditional energy sources—wind
plus electricity, geothermal plus electricity, solar plus electricity, biomass plus
electricity, solar, wind plus electricity, and solar biomass plus electricity—have
been selected. These types of energy generation technologies are the most suitable
in the sector of private housing. Such combinations of technologies are suitable in
the climate zones where the most important types of energy in buildings are
heating and hot water preparation (the Baltic states, for instance).
When a set of criteria must describe certain alternatives, quantifiable criteria are
not enough. A need is growing to consider how the alternatives comply with
environmental goals, the principles of sustainable development and public
expectations. Adding qualitative criteria makes it possible to develop a more
flexible
system
that
makes
an
integrated
analysis
of
changing
environment
(Sliogeriene et al.
2012
).
The set of criteria in the EGT-PH-DSS comprises five quantitative criteria
expressed by quantitative measuring units (''Investments in energy supply sour-
ces'', ''Heating cost'', ''Payback time'', ''Share of renewable resources in the
system'', and ''Durability of system'') and seven qualitative criteria assessed in
points (''Compliance with the natural conditions'', ''Treatment of used batteries,
fuel waste'', ''Risk of accidents'', ''Innovativeness'', ''Acceptability of the envi-
ronmental aspect'', ''Acceptability of the social dimension'', and ''User-friendli-
ness, comfortable fit of system''). These criteria define four main aspects of
environment and secure system's effectiveness. Figure
5
gives a possible set of
criteria for the assessment of energy technologies.
The weights of importance of the criteria groups (technological, economic,
social and environment protection) were determined during the study, based on
Lithuanian case. According to the evaluation results, the economical and social
criteria of the energy sector are assigned with the maximum weight of importance.
The results are provided in Fig.
6
.
The decision support system includes a database and a database management
system, a model base and a model base management system, and a user interface.
The model base includes a multiple-criteria analysis model, a model of utility
degree and priority, and a recommender model. The model base management
system lets the user choose any required model. The system is designed in such
way that the results of calculations in one model are used as the input data in other
