SELECTION OF THE CONSTRICTION FACTOR FOR VENUS FLYTRAP OPTIMIZATION

This paper proposes venus flytrap optimization (VFO) with constriction factor (VFO-CF) for improving the convergence of the algorithm. The constriction factor has a significant impact on the performance of VFO-CF; its impact was inspected based on benchmark functions. Herein, the property of the constriction factor and the guidelines for determining the optimal parameter values are defined. The proposed method is tested on benchmark functions, and the obtained results are compared with existing VFO results. The water supply rate is tested in the range [4.1, 4.2], which is generally reasonable for the benchmark functions.

Economic load dispatch solutions considering multiple fuels for thermal units and generation cost of wind turbines

In this paper, economic load dispatch (ELD) problem is solved by applying a suggested improved particle swarm optimization (IPSO) for reaching the lowest total power generation cost from wind farms (WFs) and thermal units (TUs). The suggested IPSO is the modified version of Particle swarm optimization (PSO) by changing velocity and position updates. The five best solutions are employed to replace the so-far best position of each particle in velocity update mechanism and the five best solutions are used to replace previous position of each particle in position update. In addition, constriction factor is also used in the suggested IPSO. PSO, constriction factor-based PSO (CFPSO) and bat optimization algorithm (BOA) are also run for comparisons. Two systems are used to run the four methods. The first system is comprised of nine TUs with multiple fuels and one wind farm. The second system is comprised of eight TUs with multiple fuels and two WFs. From the comparisons of results, IPSO is much more powerful than three others and it can find optimal power generation with the lowest total power generation cost.

RELIABLE QUANTIFICATION OF PORE GEOMETRY IN CARBONATE ROCKS USING NMR AND ELECTRICAL RESISTIVITY MEASUREMENTS FOR ENHANCED ASSESSMENT OF PERMEABILITY AND CAPILLARY PRESSURE

Reliable and real-time assessment of directional permeability and saturation-dependent capillary pressure are utterly important because they significantly affect the exploitation strategies. Conventional well-log-based methods (e.g., NMR-based, saturation-height analysis, resistivity-based, correlation-based) are either highly dependent on calibration efforts or rely on model parameters which are difficult to obtain in real-time and make them dependent on core measurements. Moreover, most conventional methods for assessment of directional permeability and saturation-dependent capillary pressure fail in the presence of multi-modal pore-size distribution. Recent publications suggested that integration of transverse Nuclear Magnetic Resonance (T2 NMR) and resistivity measurements enables assessment of pore-throat-size distribution as well as permeability and capillary pressure. However, the reliability of these methods is questionable in rocks with complex/multi-modal pore geometry. The objectives of this paper include (a) reliably estimating a variable constriction factor (a geometric parameter which relates the pore- and throat-size) in rocks with complex pore geometry to accurately quantify pore geometry, which is the main contribution of this work, (b) developing a new rock physics workflow for integrating NMR and electrical conductivity for assessment of permeability and capillary pressure that takes into account a variable constriction factor, and (c) verifying the reliability of the introduced workflow using core scale measurements. The proposed workflow starts with calculating pore-body-size distribution from NMR T2 distribution. Then, we combine electrical resistivity and pore-size distribution to estimate the distribution of constriction factor in the pore structure. Next, we determine pore- throat-size distribution using the estimated variable constriction factor. We then introduce a new permeability model which takes variable constriction factor into account. The inputs to the permeability model include throat-size distribution, tortuosity, and porosity. Finally, we calculate saturation-dependent capillary pressure using the estimated throat-size distribution. We successfully verified the reliability of the introduced workflow in the core-scale domain in carbonate rock samples with complex pore structure. The permeability estimates obtained by the new workflow yielded less than 7% average relative error when compared against core measurements. We also observed a good agreement between the throat-size distribution and capillary pressure estimated from the new workflow and the ones acquired from MICP (mercury injection capillary pressure) measurements. Results also confirmed that integration of a variable constriction factor improves directional permeability estimates compared to cases where an effective constriction factor was used to quantify pore-throat size distribution in rocks with multi-modal pore-size distribution.

An Efficient Hybrid Method for Solving Security-Constrained Optimal Power Flow Problem

The optimal operation for different states such as normal and contingency cases of a power system has a very important role in the operation. Therefore, it is necessary to analyze contingencies in the system so as the most severe cases should be considered for integrating into the optimal power flow (OPF) problem and the security-constrained optimal power flow (SCOPF) becomes an important problem for considering in the power system operation. This paper proposes a combined pseudo-gradient based particle swarm optimization with constriction factor (PGPSO) and the differential evolution (DE) method for solving the SCOPF problem. The PGPSO-DE method is a newly developed method for utilizing the advantages of the pseudogradient guided PSO method with a constriction factor and the DE method. The proposed PGPSO-DE has been tested on the IEEE 30 bus system for the normal case and the contingency case with two types of the objective function. The results yielded from the proposed method have been validated via comparing to those from the conventional PSO, DE, and other methods reported in the literature. The comparisons for the results obtained from the proposed PGPSODE method have shown that it is very effective to solve the large-scale and complex SCOPF problem.