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Indices to Assess the Integration of Renewable Energy Resources on Transmission Systems

DOI: 10.1155/2013/324562

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The continuous increase on the penetration levels of Renewable Energy Sources (RESs) in power systems has led to radical changes on the design, operation, and control of the electrical network. This paper investigates the influence of these changes on the operation of a transmission network by developing a set of indices, spanning from power losses to GHG emissions reduction. These indices are attempting to quantify any impacts therefore providing a tool for assessing the RES penetration in transmission networks, mainly for isolated systems. These individual indices are assigned an analogous weight and are mingled to provide a single multiobjective index that performs a final evaluation. These indices are used to evaluate the impact of the integration of RES into the classic WSCC 3-machine, 9-bus transmission network. 1. Introduction European Union countries have a set of specific targets to promote the use of energy from Renewable Energy Source (RES) in accordance with the Directive 2009/28/EC of the European Parliament [1]. These National Action Plans (NAPs) consider and set targets for the final use of energy for heating and cooling, electricity generation, and transportation. In particular, electricity generation is of great interest as it requires the liberalization of the electricity markets. The 16% of global final energy consumption comes from renewable sources during 2012, with 10% coming from traditional biomass, which is mainly used for heating and 3.4% from hydroelectricity. New renewable sources (small hydro, modern biomass, wind, solar, geothermal, and biofuels) accounted for another 2.8% and are growing very rapidly [2]. The share of renewable sources in electricity generation is around 19%, with 16% of global electricity coming from hydroelectricity and 3% from new renewable sources [2]. Nevertheless, RESs have not been a significant part of the energy mix for the vast majority of countries around the world, fact which has led governments to provide incentives to entities that are interested in investing in RES electricity generation, in most cases using wind and solar power. Consequently, it is of crucial importance to investigate how RES generation affects the network’s operational ability and which potential configurations could prove beneficial. Hence, a series of technical aspects must be considered by the planners in order to evaluate the pros and cons of such penetration. In particular, the minimization of power losses has so far been the most important issue for the planners [3, 4]. However, other grid related technical aspects


[1]  T. E. Parliament and the Council of the European Union, “Directive 2009/28/EC of the European parliament and of the council on the promotion of the use of energy from renewable sources and amending and subsequently repealing directives 2001/77/EC and_2003/30/EC,” Official Journal of the European Union, vol. L140, pp. 17–62, 2009.
[2]  REN21, “Renewable 2011 Global Status Report,” Tech. Rep., Paris, France, 2011.
[3]  F. Gonzalez-Longatt, “Impact of distributed generation over power losses on distribution system,” in Proceedings of the 9th International Conference on Electrical Power Quality and Utilization, Barcelona, Spain, October of 2007.
[4]  A. D. T. Le, M. A. Kashem, M. Negnevitsky, and G. Ledwich, “Optimal distributed generation parameters for reducing losses with economic consideration,” in Proceedings of IEEE Power Engineering Society General Meeting (PES '07), pp. 1–8, June 2007.
[5]  L. F. Ochoa, A. Padilha-Feltrin, and G. P. Harrison, “Evaluating distributed generation impacts with a multiobjective index,” IEEE Transactions on Power Delivery, vol. 21, no. 3, pp. 1452–1458, 2006.
[6]  A. Keane and M. O'Malley, “Optimal allocation of embedded generation on distribution networks,” IEEE Transactions on Power Systems, vol. 20, no. 3, pp. 1640–1646, 2005.
[7]  A. J. Wood and B. F. Wollenberg, Power Generation, Operation and Control, Wiley Interscience, 2nd edition, 1996.
[8]  F. Bouffard and F. D. Galiana, “An electricity market with a probabilistic spinning reserve criterion,” IEEE Transactions on Power Systems, vol. 19, no. 1, pp. 300–307, 2004.
[9]  A. M. L. da Silva, W. S. Sales, L. A. da Fonseca Manso, and R. Billinton, “Long-term probabilistic evaluation of operating reserve requirements with renewable sources,” IEEE Transactions on Power Systems, vol. 25, no. 1, pp. 106–116, 2010.
[10]  P. M. Anderson and A. A. Fouad, Power System Control and Stability, IEEE Press, New York, NY, USA, 2nd edition, 2003.
[11]  A. Poullikas, Independent Power Producer Technology, Selection Algorithm, Software for Power Technology Selection in Competitive Electricity Markets, 2nd edition, 2000–2005.
[12]  R. D. Zimmerman, C. E. Murillo-Sanchez, and D. Gan, “MATPOWER download,”
[13]  K. Bhattacharya and J. Zhong, “Reactive power as an ancillary service,” IEEE Transactions on Power Systems, vol. 16, no. 2, pp. 294–300, 2001.


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