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Optimal activity and battery scheduling algorithm using load and solar generation forecasts
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AI
DOI：10.1109/AUPEC58309.2022.10215582.png)
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Abstract
En 中文
Energy usage optimal scheduling has attracted great attention in the power system community, where various methodologies have been proposed. However, in real-world applications, the optimal scheduling problems require reliable energy forecasting, which is scarcely discussed as a joint solution to the scheduling problem. The 5th IEEE Computational Intelligence Society (IEEE-CIS) competition raised a practical problem of decreasing the electricity bill by scheduling building activities, where forecasting the solar energy generation and building consumption is a necessity. To solve this problem, we propose a technical sequence for tackling the solar PV and demand forecast and optimal scheduling problems, where solar generation prediction methods and an optimal university lectures scheduling algorithm are proposed.
Keywords:
Forecasting
Refined motif
Optimisation
Valley-filling scheduling
Mixed-integer linear programming (MILP)
Journal
A
IF:
0
Papers:
26
Citations:
0