A high wind-power penetration level causes increased uncertainty in power system operation because of the variability and limited predictability of wind generation. This paper proposes a novel type of unit commitment (UC) considering spinning reserve and interruptible load (IL) as operating reserve facilities to increase system flexibility for reliable, economical operation. Two uncertainty sources, load and wind generation, were modeled via autoregressive moving averages (ARMA). The formulation of interruptible load was considered in the implementation of unit commitments. Lagrangian relaxation-dynamic programming (LR-DP) was used to solve the unit commitment problem efficiently. The expected energy not supplied (EENS) was regarded as a probabilistic reliability criterion. The effectiveness of the proposed unit commitment was evaluated using an IEEE 118-bus system. The simulation results clearly demonstrated that with demand-side participation, the operating cost was significantly reduced when handling the increased uncertainty due to wind power integration within the required reliability criteria.

This paper presents a novel probabilistic optimization algorithm for simultaneous active and reactive power dispatch in power systems with significant wind power integration. Two types of load and wind-speed uncertainties have been assumed that follow normal and Weibull distributions, respectively. A PV bus model for wind turbines and the wake effect for correlated wind speed are used to achieve accurate AC power flow analysis. The power dispatch algorithm for a wind-power integrated system is modeled as a probabilistic optimal power flow (P-OPF) problem, which is operated through fixed power factor control to supply reactive power. The proposed P-OPF framework also considers emission information, which clearly reflects the impact of the energy source on the environment. The P-OPF was tested on a modified IEEE 118-bus system with two wind farms. The results show that the proposed technique provides better system operation performance evaluation, which is helpful in making decisions about power system optimal dispatch under conditions of uncertainty.