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.