Improving the performance of power systems has become a challenging task for system operators in an open access environment. This paper presents an optimization approach for solving the multi-objective scheduling problem using a modified non-dominated sorting genetic algorithm in a hybrid network of meshed alternating current (AC)/wind farm grids. This approach considers voltage and power contr...

Security-constrained unit commitment (SCUC) model is used for power system day-ahead scheduling. However, current SCUC uses a static network to deliver and meet demand optimally. A dynamic can provide lower optimal cost alleviate congestion. due the computational complexity lack of effective algorithms, reconfiguration has not been included in yet. This paper presents novel approach handle secu...

State forecasting is a powerful tool to enhance the noise suppression ability of the state estimation process of a power system. Artificial neural networks can perceive complex nonlinear interactions among variables that improve the predictions accuracy and robustness. This paper investigates the applicability of artificial neural networks to state forecasting . Nonlinear autoregressive neural ...

With large-scale integration of renewable generation, energy storage is expected to play an important role in providing flexibility systems. In this paper, the authors construct a trilevel Stackelberg game model study co-investment merchant and regulated reserve markets. The upper-level problem profit-maximizing investment with desired rate-of-return solved by investor. middle-level problem, sy...

In this paper, we presents a novel approach for solving optimal power flow (OPF) problems using a hybrid differential evolution and harmony search (DEHS). The DEHS method is an improved differential evolution method based on the harmony search scheme. Harmony Search has strong and easy to combine with other methods in optimization and the Differential Evolution algorithm has a very great abilit...

This paper presents a voltage stability constrained optimal power flow that is expressed via a bilevel programming framework. The inner objective function is dedicated for maximizing voltage stability margin while the outer objective function is focused on minimization of total production cost of thermal units. The original two stage problem is converted to a single level optimization problem v...

Recently, smart grids have been considered as one of the vital elements in upgrading current power systems to a system with more reliability and efficiency. Distributed generation is necessary for most of these new networks. Indeed, in all cases that DGs are used in distribution systems, protection coordination failures may occur in multiple configurations of smart grids using DGs. In different...

Congestion cost allocation is an important issue in congestion management. This paper presents a genetic algorithm (GA) to determine the optimal generation levels in a deregulated market. The main issue is congestion in lines, which limits transfer capability of a system with available generation capacity. Nodal pricing method is used to determine locational marginal price (LMP) of each generat...

Voltage stability is one of the most important factors in maintaining reliable operation of power systems. When a disturbance occurs in the power system, it usually causes instabilities and sometimes leads to voltage collapse (VC). To avoid such problems, a novel approach called Vector Analysis (VA) is proposed that exploits a new instability detection index to provide wide area voltage stabili...

This paper presents a method to allocate the transmission network costs to users based on nodal pricing approach by regulating the nodal prices from the marginal point to the new point. Transmission nodal pricing based on marginal prices is not able to produce enough revenue to recover the total transmission network costs. However, according to the previous studies in this context, this met...