  In this paper we formulate an optimization approach to schedule electrical
loads given a short term prediction of time-varying power production and the
ability to store only a limited amount of electrical energy. The proposed
approach is unique and versatile as it allows scheduling of electrical loads
that each have their own dynamic power demand during on/off switching, while
also allowing the specification of minimum on/off times for each loads
separately. The optimization approach is formulated as a parallel enumeration
of all possible on/off times of the electrical loads using a moving time
approach in which only a short term power production forecast is needed, while
at the same time taking into account constraints on electrical energy storage
and power delivery of a battery system. It is shown that the complexity of the
optimization (number of enumerations) is limited by the number of data points
in the short term power production forecast and the minimum on/off time of the
electrical loads. The limited complexity along with parallel enumeration allows
real-time operational scheduling of a large number of loads. The simulation
results shown in this paper illustrate that relatively short term power
forecast profiles can be used to effectively schedule dynamic loads with
various dynamic load profiles.
