Fitiwi, Desta Z. and Lynch, Muireann and Bertsch, Valentin (2019) Optimal development of electricity generation mix considering fossil fuel phase-out and strategic multi-area interconnection. ESRI WP616, February 2019. [Working Paper]
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Abstract
Increased renewable generation worldwide is posing new challenges for power system planners. The location, as well as the level and operation, of each generation resource is increasingly important. This work presents a constrained Generation Expansion Planning (GEP) optimization model. One of the salient features of the model is its reasonably accurate representation of the physical characteristics of power systems. It considers both active and reactive power flows in a linear manner. Natural voltage magnitude deviations from nominal values across the transmission system are also captured in the resulting model. Therefore, the network model employed here closely resembles the AC optimal power flow one.We apply the model to a realistic test system of the island of Ireland and determine the optimal generation expansion and operation out to 2030 under a range of demand and policy scenarios. Our results show that costs and emissions are driven primarily by the decommissioning of old inefficient generation units. High renewable targets, on the other hand, render increased carbon prices relatively ineffective in reducing system emissions.
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Item Type: | Working Paper |
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Subjects for non-EU documents: | EU policies and themes > Policies & related activities > energy policy (Including international arena) EU policies and themes > Policies & related activities > environmental policy (including international arena) Countries > Ireland |
Subjects for EU documents: | UNSPECIFIED |
EU Series and Periodicals: | UNSPECIFIED |
EU Annual Reports: | UNSPECIFIED |
Series: | Series > Economic and Social Research Institute (ESRI), Dublin > ESRI Working Papers |
Depositing User: | Phil Wilkin |
Official EU Document: | No |
Language: | English |
Date Deposited: | 26 Dec 2019 13:40 |
Number of Pages: | 34 |
Last Modified: | 26 Dec 2019 13:40 |
URI: | http://aei.pitt.edu/id/eprint/102229 |
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