Approximations made in day-ahead markets can result in suboptimal or even infeasible schedules for generating units and inaccurate predictions of actual costs and wind curtailment. Here we compare different optimal models of day-ahead markets based on unit commitment (UC) formulations, especially energyvs. power-based UC; excluding or including startup and shutdown trajectories; and determinist...

This paper proposes a methodology to limit the variations in generation cost in a power system under normal and contingent state using Differential Evolution (DE) optimization technique keeping consumer welfare in view. The aim of this proposed methodology is to minimize the deviations of generation cost, during contingency, from a preferred value by rescheduling of the generation with a contro...

This paper presents a new approach for state adequacy evaluation of sampled system state in composite power system reliability analysis. Generalized regression neural network (GRNN) is used in conjunction with non-sequential Monte Carlo simulation (MCS) to evaluate the loss of probability and the power indices. GRNN approach predicts the test functions for all the sampled states after sufficien...

In this paper security constrained unit commitment (SCUC) is employed for simultaneous clearing of energy and reserve markets. Spinning reserve of production units and interruptible loads (IL) are used as system operation reserve. Some restrictions on the use of interruptible loads, such as maximum load curtailed, maximum curtailment hour in a day, maximum length of each curtailment are also co...

The requirement for minimized cost whilst preserving power system reliability necessitates the development of both efficient system security assessment approaches and appropriate emergency remedial actions. Load shedding is a type of corrective actions that is applied to save power system stability against severe disturbances. This paper proposes an optimal load shedding policy that takes into ...

In this paper, a novel method based on Hybrid Genetic Algorithm and Particle Swarm Optimization (HGAPSO) technique is proposed for solving Under Voltage Load Shedding (UVLS) problem. Load curtailment as ultimate control action is performed by under voltage load shedding scheme to guarantee power system voltage stability in contingency conditions. In addition, the proposed under voltage load she...