Balancing renewable energy costs and optimizing energy mix
The authors consider wind, solar, hydraulic, nuclear, coal and gas as potential energy sources. In their model, the energy demand and availability are cast as random variables. The authors simulated the behaviour of the mix for a large number of tests of such variables, using so-called Monte-Carlo simulations.
For a given mix, they found the energy cost of the mix presents a minimum as a function of the installed power. This means that if it is too large, the fixed costs dominate the total and become overwhelming. In contrast, if it is too small, expensive energy sources need to be frequently solicited.
The authors are also able to optimise the energy mix, according to three selected criteria, namely economy, environment and supply security.
The simulation tested on the case of France, based on 2011 data, shows that an optimal mix is 2.4 times the average demand in this territory. This mix contains a large amount of nuclear power, and a small amount of fluctuating energies: wind and solar. It is also strongly export-oriented.
- Bernard Bonin, Henri Safa, Axel Laureau, Elsa Merle-Lucotte, Joachim Miss, Yann Richet. MIXOPTIM: A tool for the evaluation and the optimization of the electricity mix in a territory. The European Physical Journal Plus, 2014; 129 (9) DOI: 10.1140/epjp/i2014-14198-7