A regional energy planning methodology including renewable energy sources and environmental constraints
In this paper, a bottom-up energy system optimisation model is proposed in order to support planning policies for promoting the use of renewable energy sources. A linear programming optimisation methodology based on the energy flow optimisation model (EFOM) is adopted, detailing the primary energy sources exploitation (including biomass, solid waste, process by-products), power and heat generation, emissions and end-use sectors. The modelling framework is enhanced in order to adapt the model to the characteristics and requirements of the region under investigation. In particular, a detailed description of the industrial cogeneration system, that turns out to be the more efficient and increasingly spread, is incorporated in the regional model. The optimisation process, aiming to reduce environmental impact and economical efforts, provides feasible generation settlements that take into account the installation of combined cycle power plants, wind power, solid-waste and biomass exploitation together with industrial combined heat and power (CHP) systems. The proposed methodology is applied to case of the Apulia region in the Southern Italy.
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Volume (Year): 7 (2003)
Issue (Month): 2 (April)
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References listed on IDEAS
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- Wene, Clas-Otto & Ryden, Bo, 1988. "A comprehensive energy model in the municipal energy planning process," European Journal of Operational Research, Elsevier, vol. 33(2), pages 212-222, January.
- Grohnheit, Poul Erik, 1991. "Economic interpretation of the EFOM model," Energy Economics, Elsevier, vol. 13(2), pages 143-152, April.
- Salem Szklo, Alexandre & Borghetti Soares, Jeferson & Tiomno Tolmasquim, Maurício, 2000. "Economic potential of natural gas-fired cogeneration in Brazil: two case studies," Applied Energy, Elsevier, vol. 67(3), pages 245-263, November.
- Kanudia, Amit & Loulou, Richard, 1998. "Robust responses to climate change via stochastic MARKAL: The case of Quebec," European Journal of Operational Research, Elsevier, vol. 106(1), pages 15-30, April.
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