Stochastic Based Reactive Power Market in Deregulated Environment

摘要

This paper presents a stochastic reactive power market in deregulated power systems in which the uncertainties of load forecast, generating units as well as transmission lines are taken into account. At first, Lattice Monte Carlo Simulation (LMCS) is used to generate random scenarios. The roulette while mechanism is implemented to generate the load of each scenario. In order to reduce computation burden, the scenario reduction technique is implemented to select only the most probable scenario and discard the similar ones and those with low probability. After scenario reduction, the stochastic reactive power market is cleared in the form of a series of deterministic optimization problems, including the non-contingent scenario and different post-contingency states. The objective function is to minimize the expected value of total payment function (TPF) of generators in dollars paid to the generators for their reactive power compensation. The proposed stochastic reactive power market is studied based on the IEEE 24-bus Reliability Test System.