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Robust optimization of forecast combinations

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Post, Thierry

Arvanitis, Stelios

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NO

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In this paper, we introduce RF energy harvesting paradigm into WNCS framework to study the optimal power control, energy harvesting and scheduling problem with the objective of providing maximum level of adaptivity under strict timing and reliability requirements employing the constant rate transmission model. We formulate the problem as a Mixed Integer Linear Programming Problem (MILP). We show the power allocation can be separated from the scheduling and harvesting at optimality. Then, we introduce a heuristic algorithm for the scheduling problem, periodic list scheduling (PLS), inspired from list scheduling of jobs with sequence dependent setup times on identical machines. We then demonstrate via extensive simulations the superiority of the proposed algorithm in terms of closeness to the optimal, adaptivity and runtime.

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Elsevier

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International Journal of Forecasting

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10.1016/j.ijforecast.2019.01.007

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Item type:Goal, Access status: Open Access ,
07 - Affordable and Clean Energy
Renewable energy solutions are becoming cheaper, more reliable and more efficient every day.Our current reliance on fossil fuels is unsustainable and harmful to the planet, which is why we have to change the way we produce and consume energy. Implementing these new energy solutions as fast as possible is essential to counter climate change, one of the biggest threats to our own survival.
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