Microgrids (MGs), which predominantly consist of renewable energy sources, play a significant role in achieving this objective. This paper proposes an optimized methodology for power dispatch in MGs using mixed-integer linear programming (MILP). In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. A Wasserstein ambiguity set is constructed to support data-driven decision-making. By fully leveraging the special structure of worst-case expectation from the. For the dispatch of practical microgrids, power loss from energy conversion devices should be considered to improve the efficiency. The code is available under the MIT. Existing literature on two-stage robust planning for wind-powered microgrids has overlooked the substantial differences in fluctuation ratios of small-capacity wind power across different time scales. Your purchase has been completed. Rodrigues Lautert, Renata, Cambambi, Cláudio Adriano C.
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