  This paper presents a coordinative demand charge mitigation (DCM) strategy
for reducing electricity consumption during system peak periods. Available DCM
resources include batteries, diesel generators, controllable loads, and
conservation voltage reduction. All resources are directly controlled by load
serving entities. A mixed integer linear programming based energy management
algorithm is developed to optimally coordinate of DCM resources considering the
load payback effect. To better capture system peak periods, two different kinds
of load forecast are used: the day-ahead load forecast and the peak-hour
probability forecast. Five DCM strategies are compared for reconciling the
discrepancy between the two forecasting results. The DCM strategies are tested
using actual utility data. Simulation results show that the proposed algorithm
can effectively mitigate the demand charge while preventing the system peak
from being shifted to the payback hours. We also identify the diminishing
return effect, which can help load serving entities optimize the size of their
DCM resources.
