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Abstract-Demand response is an important part of the smart grid technologies. This is a particularly interesting problem with the availability of dynamic energy pricing models. Electricity consumers are encouraged to consume electricity more prudently in order to minimize their electric bill, which is in turn calculated based on dynamic energy prices. In this paper, task scheduling policies that help consumers minimize their electrical energy cost by setting the time of use (TOU) of energy in the facility. Moreover, the utility companies can reasonably expect that their customers reduce their consumption at critical times in response to higher energy prices during those times. These policies target two different scenarios: (i) scheduling with a TOU-dependent energy pricing function subject to a constraint on total power consumption; and (ii) scheduling with a TOU and total power consumption-dependent pricing function for electricity consumption. Exact solutions (based on Branch and Bound) are presented for these task scheduling problems. In addition, a rank-based heuristic and a force directed-based heuristic are presented to efficiently solve the aforesaid problems. The proposed heuristic solutions are demonstrated to have very high quality and competitive performance compared to the exact solutions. Moreover, ability of demand shaping utilizing the aforementioned pricing schemes is demonstrated by the simulation results.

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