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Energy usage optimal scheduling has attracted great attention in the powersystem community, where various methodologies have been proposed. However, inreal-world applications, the optimal scheduling problems require reliableenergy forecasting, which is scarcely discussed as a joint solution to thescheduling problem. The 5\textsuperscript{th} IEEE Computational IntelligenceSociety (IEEE-CIS) competition raised a practical problem of decreasing theelectricity bill by scheduling building activities, where forecasting the solarenergy generation and building consumption is a necessity. To solve thisproblem, we propose a technical sequence for tackling the solar PV and demandforecast and optimal scheduling problems, where solar generation predictionmethods and an optimal university lectures scheduling algorithm are proposed.

Optimal activity and battery scheduling algorithm using load and solar generation forecasts