The current awareness of the depletion in the fossil fuels reserves and the effect of
green house gases (GHG) toward global warming has motivated many researchers in
the area of energy system modelling. This thesis presents mathematical models to aid
decision makers in determining the optimal spatially aggregated energy supply chain
network to satisfy the future energy demand at the national level.
Firstly, the energy planning problem using Thailand’s energy system as the case study
is addressed by the development of a multi-period environmentally conscious
deterministic energy system optimisation model. The model is formulated as a linear
programming (LP) model that can address decision-making of the optimal future
energy supply chain network at the national level with consideration of the scale of
GHG emissions of the network. The determination of data required for the
development of the proposed model is also tackled.
Secondly, the reformulation of the multi-period deterministic model as a three-staged
stochastic energy system optimisation model that can support decision-making under
uncertainty in energy demand is addressed.
Further extensions to the deterministic model include its reformulation to take into
account the geographical location of an energy system. The linear programming
model is reformulated as a mixed integer linear programming model (MILP) that can
incorporated the spatial nature of the energy system as part of the decision-making
process. The decisions to be determined include: (1) scale, type and location of energy
production facility, (2) scale and type of resource usage in each location, (3) flow of resources and energy between grids to satisfy the energy demand throughout the
planning horizon.
Next, the Biomass-to-Energy supply chain network over long-term planning with
application to Thailand is focused, based on the spatial MILP formulation. A higher
complexity of geographical location is addressed as well as increases in types of
biomass and biomass thermal conversion technologies. The objective function is
modified to maximise the total network profit rather than minimising the total
network costs.
Finally, the long-term planning of a Waste-to Energy supply chain network with
application to Thailand is investigated. The Waste-to-Energy system is addressed in
view of investors as decision-makers as the objective function is also to maximise the
total profit of the network. Different network structures of converting waste into
energy are applied. The problem is also formulated as a MILP problem.
This thesis reveals that, based on the model assumptions, the optimal environmentally
conscious energy supply chain networks rely heavily on the utilisation of renewable
resources throughout the country. With the abundant amount of biomass and waste
resources available in Thailand, Biomass and Waste-to-Energy projects have a high
potential in diversifying the use of fossil fuels as primary energy sources in Thailand.