  Minimizing the peak power consumption and matching demand to supply, under
fixed threshold polices, are two key requirements for the success of the future
electricity market. In this work, we consider dynamic pricing methods to
minimize the peak load and match demand to supply in the smart grid. As these
optimization problems are computationally hard to solve in general, we propose
generic heuristics for approximating their solutions. Further, we provide
theoretical analysis of uniform pricing in peak-demand minimization. Moreover,
we propose optimal-pricing algorithms for scenarios in which the time-period in
which tasks must be executed is relatively small. Finally, we conduct several
experiments to evaluate the various algorithms on real data.
