Conference article

An Optimization Model for the Integration of Renewable Technologies in Power Generation Systems

Andreas Poullikkas
Electricity Authority of Cyprus, Cyprus

Download articlehttp://dx.doi.org/10.3384/ecp110572347

Published in: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden

Linköping Electronic Conference Proceedings 57:9, p. 2347-2354

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Published: 2011-11-03

ISBN: 978-91-7393-070-3

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

In view of the expanding Renewable Energy Sources (RES) generation worldwide and in particular in European Union; it is crucial for every country to consider the cost of integrating the necessary mixture of RESE technologies in their existing and future generation systems. In this work; an optimization model for the integration of RES electricity (RES-E) technologies in power generation systems is developed. The purpose of the optimization procedure is to assess the unavoidable increase in the cost of electricity of a given power generation system at different RES-E penetration levels. The optimization model developed uses a genetic algorithm (GA) technique for the calculation of both the additional cost of electricity due to the large penetration of RES-E technologies as well as the required RES-E levy in the electricity bills in order to fund this RES-E penetration. The above GA procedure enables the estimation of the level of the adequate (or eligible) feed-intariff (FiT) to be offered to future RES-E systems. The overall cost increase in the electricity sector for the promotion of RES-E technologies; for a given period; is analyzed taking into account factors; such as; the fuel avoidance cost; the carbon dioxide emissions avoidance cost; the conventional power system increased operation cost; etc. The applicability of the developed optimization model is applied to the small isolated power generation system of the island of Cyprus. The results indicated that in the case of 15% RES-E penetration by providing FiTs with a 10% internal rate of return the required level of RES-E levy in the electricity bills will be 0.53€c/kWh.

Keywords

Power generation; renewable energy sources; genetic algorithm; optimization

References

[1] European Commission; Renewable Energy Road Map - Renewable energies in the 21st century: building a more sustainable future; 2006; COM(2006) 248.

[2] European Commission; Barcelona Process: Union for the Mediterranean; 2008; COM(2008) 319.

[3] European Commission; Commission Decision of 30 June 2009 establishing a template for National Renewable Energy Action Plans under Directive 2009/28/EC of the European Parliament and of the Council; 2009; 2009/548/EC.

[4] European Commission; Directive 2009/28/EC of the European Parliament and of the Council 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC; 2009.

[5] Poullikkas A.; I.P.P. ALGORITHM v2.1; Software for power technology selection in competitive electricity markets; 2006; © 2000 – 2006; User Manual.

[6] Poullikkas A.; “Implementation of distributed generation technologies in isolated power systems”; Renewable and Sustainable Energy Reviews; 2007; 11; pp. 30-56. doi: 10.1016/j.rser.2006.01.006.

[7] Poullikkas A.; “A decouple optimization method for power technology selection in competitive markets”; Energy Sources; 2009; Part B; 4; pp. 199-211.

[8] Poullikkas A.; 2009; “Economic analysis of power generation from parabolic trough solar thermal plants for the Mediterranean region – A case study for the island of Cyprus”; Renewable and Sustainable Energy Reviews; 13; pp. 2474-2484. doi: 10.1016/j.rser.2009.03.014.

[9] Poullikkas A.; 2009; Introduction to Power Generation Technologies; NOVA Science Publishers; Inc.; New York; ISBN: 978-1-60876-472-3.

[10] Poullikkas A.; Hadjipaschalis I.; Kourtis G.; 2010; “The cost of integration of parabolic trough CSP plants in isolated Mediterranean power systems”; Renewable and Sustainable Energy Reviews; 14; pp. 1469–1476. doi: 10.1016/j.rser.2010.01.003.

[11] Wien Automatic System Planning (WASP) Package: A Computer Code for Power Generating System Expansion Planning Version WASP-IV with User Interface User’s Manual; 2006; International Atomic Energy Agency; Vienna.

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