  This article introduces a modified simulated annealing optimization approach
for automatically determining optimal energy management strategies in
grid-connected, storage-augmented, photovoltaics-supplied prosumer buildings
and neighbourhoods based on user-specific goals. For evaluating the modified
simulated annealing optimizer, a number of test scenarios in the field of
energy self-consumption maximization are defined and results are compared to a
gradient descent and a total state space search approach. The benchmarking
against these two reference methods demonstrates that the modified simulated
annealing approach is able to find significantly better solutions than the
gradient descent algorithm - being equal or very close to the global optimum -
with significantly less computational effort and processing time than the total
state space search approach.
