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Power System Optimization Using Mean-LPM Portfolio Theory, (CROSBI ID 619982)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Matosovic ; Marko ; Tomšić, Željko Power System Optimization Using Mean-LPM Portfolio Theory, // Conference proceeding IEEE ENERGYCON 2014 conferenc. Zagreb: IEEE ENERGYCON, 2014. str. 352-358

Podaci o odgovornosti

Matosovic ; Marko ; Tomšić, Željko

engleski

Power System Optimization Using Mean-LPM Portfolio Theory,

Optimization of power generation technology mix using portfolio theory is related to finding the optimal set of technologies under acceptable level of (price) risk which will provide minimal cost of electricity production for the generation company, or provide maximum profit. On the other hand, a generation company can set the cost of production as a fixed parameter, and then look for optimal set of technologies which would minimize price risk. The classical approach to power generation mix optimization considers renewable energy as a generation technology without price risk, or to a certain extent considers that risk being very small. In this work intermittency of renewable energy sources and accuracy in the day-ahead forecast was taken into account in the evaluation of price risk of those technologies. Energy not delivered because of wrong forecast must be bought on the balancing market and poses a burden on the price of production from those technologies. Portfolio optimization is performed using mean-LPM approach and compared to the results given by mean- variance approach. The results of the optimization show that based on the historical prices mean- variance and mean-LPM optimization give similar results only in case of second order LPM. Other orders of lower partial moments can account for risk aversion of the investor or decision maker.

Portfolio theory ; Lower partial moments ; Monte

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Podaci o prilogu

352-358.

2014.

objavljeno

Podaci o matičnoj publikaciji

Conference proceeding IEEE ENERGYCON 2014 conferenc

Zagreb: IEEE ENERGYCON

978-1-4799-2448-6

Podaci o skupu

IEEE ENERGYCON 2014 conference

predavanje

13.05.2014-16.05.2014

Cavtat, Hrvatska

Povezanost rada

Elektrotehnika