Abstract

This paper addresses the attainment of a methodology aimed at obtaining simplified models embedding the regulatory constraints imposed by the country-specific remuneration mechanisms in the energy management system of long operating life renewable assets under a high degree of uncertainty. This methodology, composed of different steps in which sensitivity analysis as well as Monte Carlo simulation play a key role, is focused on a significant case study that has implemented two of the most widely used worldwide remuneration mechanisms in the promotion of renewable energies, i.e., feed-in tariffs and auctions. The earnings before interest, tax, depreciation and amortization have been used as the output variable of the energy management model, as it is essential to take into account both revenues and operating costs of these renewable assets to manage them optimally. Some valid simplified models have been achieved by applying the proposed methodology to the case study with generalized errors below 5%. Specifically, one simplified energy management system model has been obtained under the feed-in tariff scheme, which involves acting on almost 40% of the equations of the original model and reducing the initial input parameters by 22%. Meanwhile, two simplified energy management system models have been obtained under the auction scheme. The most conservative simplified model involves acting on almost 50% of the equations of the original model and reducing the initial input parameters by 35%, while in the less conservative case it involves acting on more than 50% of the equations of the original model and reducing the initial input parameters by 42%. In short, although the uncertainty on the energy assets cannot be completely eliminated, it can be considerably reduced by facilitating the assessment of its prospective financial results. The validity of the achieved simplified models demonstrates the suitability and usefulness of the proposed simplifying methodology, providing a touch of quality in the long-term judgement and decision-making of the stakeholders when optimally managing renewable energy facilities under any type of remuneration scheme.

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