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Pricing of embedded generation: Incorporation of exernalities and avoided network losses

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dc.contributor.author Rodrigo, AS
dc.contributor.author Wijayatunga, PDC
dc.date.accessioned 2013-10-21T02:29:09Z
dc.date.available 2013-10-21T02:29:09Z
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/8664
dc.description.abstract Traditionally, the electricity purchase tariff of embedded generators reflected only the cost of production and delivery of electricity to the consumers, which includes the costs of labor, capital, operation, taxes and insurance. However, the production of electricity causes adverse impacts on the environment. At present, this issue has not been widely addressed by the existing pricing methodologies. This paper proposes a pricing methodology for renewable energy based embedded electricity generation, incorporating the cost of externalities with a case study on the Sri Lanka power system. It recommends that the embedded generation tariff be based on the principle of “avoided cost”, considering the cost of energy production, cost of externalities and the cost of network losses. While the “impact path way” approach is proposed for calculation of the cost of externalities of energy, the nodal‐based cost calculation is proposed for the avoided cost of network losses calculation. The pricing methodology proposed in the paper provides important information for investors when choosing the most economical site for their development. It can also be used to optimize the network use. These will allow the developers of embedded generation facilities and the utilities operating the national grid to maximize the potential of embedded generation.
dc.language en
dc.subject Pricing of embedded generation
dc.subject Avoided cost
dc.subject Costing of externalities
dc.title Pricing of embedded generation: Incorporation of exernalities and avoided network losses
dc.type Article-Abstract
dc.identifier.year 2007
dc.identifier.journal Energy Conversion and Management|
dc.identifier.issue 8
dc.identifier.volume 48
dc.identifier.pgnos 2332-2340


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