Solving Hydropower Unit Commitment Problem Using a Novel Sequential Mixed Integer Linear Programming Approach

Hydro Unit Commitment (HUC) is an important problem of power systems and when it is dealt with via a mathematical programming approach and optimization, it leads to the complicated class of mixed-integer nonlinear programming (MINLP). Many attempts have been made to solve the problem efficiently, while there is still ongoing research to come up with better solution schemes in terms of runtime and optimality. Highly nonlinear nature of the relationships and constraints in the optimization problem have forced the researchers to deal with the HUC problem in simplified manners which may result in impractical and unreliable solutions, i.e. schedules. Here in this paper we proposed a new method based on sequential mixed-integer linear programming (MILP) for solving a more realistic version of the HUC problem efficiently. We applied the proposed method to a cascade of two hydropower plants, Karun-3 and Karun-4, located in the Southwest of Iran. The sequential MILP approach was compared with several MINLP solvers of the GAMS optimization package. The results indicated that the proposed methodology outperformed the MINLP solvers in terms of efficiency, with solution time of less than 30 s, compared to 10 min that were given to the solvers, and in terms of optimality with more than 20 thousand cubic meters per day in water release. Additionally, we have explored the effect of penalizing the total number of startups on the total release, convergence of the algorithm, and the computation time. In all of the cases the total number of startups was reduced more than three times.

     

A high-performance four-node flat shell element with drilling degrees of freedom

Engineering with Computers - This paper presents a new four-node quadrilateral flat shell element, named QFSUQ, for analysis of shell structures. The element is formed by assemblage of a new...     

Efficient Flight Control via Mechanical Impedance Manipulation: Energy Analyses for Hummingbird-Inspired MAVs

Within the growing family of unmanned aerial vehicles (UAV), flapping-wing micro aerial vehicles (MAV) are a relatively new field of research. Inspired by small size and agile flight of insects and birds, these systems offer a great potential for applications such as reconnaissance, surveillance, search and rescue, mapping, etc. Nevertheless, practicality of these vehicles depends on how we address various challenges ranging from control methodology to morphological construction and power supply design. A reasonable approach to resolving such problems is to acquire further inspiration from solutions in nature. Through modeling synchronous muscles in insects, we have shown that manipulation of mechanical impedance properties at wing joints can be a very efficient method for controlling lift and thrust production in flapping-wing MAVs. In the present work, we describe how this approach can be used to decouple lift/thrust regulation, thus reducing the complexity of flight controller. Although of simple design, this controller is still capable of demonstrating a high degree of precision and maneuverability throughout various simulated flight experiments with different types of trajectories. Furthermore, we use these flight simulations to investigate the power requirements of our control approach. The results indicate that these characteristics are considerably lower compared to when conventional control strategies—methods that often rely on manipulating stroke properties such as frequency or magnitude of the flapping motion—are employed. With less power demands, we believe our proposed control strategy is able to significantly improve flight time in future flapping-wing MAVs.     

Modeling Synchronous Muscle Function in Insect Flight: a Bio-Inspired Approach to Force Control in Flapping-Wing MAVs

Micro-aerial vehicles (MAV) and their promising applications—such as undetected surveillance or exploration of environments with little space for land-based maneuvers—are a well-known topic in the field of aerial robotics. Inspired by high maneuverability and agile flight of insects, over the past two decades a significant amount of effort has been dedicated to research on flapping-wing MAVs, most of which aim to address unique challenges in morphological construction, force production, and control strategy. Although remarkable solutions have been found for sufficient lift generation, effective methods for motion control still remain an open problem. The focus of this paper is to investigate general flight control mechanisms that are potentially used by real insects, thereby providing inspirations for flapping-wing MAV control. Through modeling the insect flight muscles, we show that stiffness and set point of the wing’s joint can be respectively tuned to regulate the wing’s lift and thrust forces. Therefore, employing a suitable controller with variable impedance actuators at each wing joint is a prospective approach to agile flight control of insect-inspired MAVs. The results of simulated flight experiments with one such controller are provided and support our claim.     

Topological aspects of meshless methods and nodal ordering for meshless discretizations

The meshless element‐free Galerkin method (EFGM) is considered and compared to the finite‐element method (FEM). In particular, topological aspects of meshless methods as the nodal connectivity and invertibility of matrices are studied and compared to those of the FE method. We define four associated graphs for meshless discretizations of EFGM and investigate their connectivity. The ways that the associated graphs for coupled FE‐EFG models might be defined are recommended. The associated graphs are used for nodal ordering of meshless models in order to reduce the bandwidth, profile, maximum frontwidth, and root‐mean‐square wavefront of the corresponding matrices. Finally, the associated graphs are numerically compared. Copyright © 2001 John Wiley & Sons, Ltd.     

Evaluating the effect of using different sets of enrichment for FAs on fuel management optimization using CA

In nuclear reactor core design, achieving the optimized arrangement of fuel assemblies (FAs) is the most important step towards satisfying safety and economic requirements. In most studies, nuclear fuel optimizations have been performed by using a finite number of different types of FAs. However the effect of FA numbers with different enrichments and the difference between their maximum and minimum enrichment values can be important and should be evaluated in the optimization process.     

An attempt to reconstruct the meaning of al‐Tusi's color words

In a text dating between 1259 and 1277, the Persian scholar al‐Tusi presented a systematic arrangement of 26 color terms. We propose a reconstruction of all color terms from al‐Tusi's scheme, in terms of preferred translation, mean CIEL*a^*b^* coordinates and digital representation. This reconstruction is based on a visual experiment with 30 subjects, who identified the Munsell chip best representing each color term. Persian words for which the meaning changed since the time of al‐Tusi were substituted by direct translations. The results show considerable interobserver variability in the colors selected when identifying color terms. This relatively large variation was shown to be a characteristic for memory matching experiments in general. Several specific color terms for which the resulting color variation was particularly large are discussed in more detail, and possible explanations for these variations are proposed. The proposed reconstruction suggests that al‐Tusi's list is largely consistent in modern colorimetric terms, although some large hue shifts are observed for color terms corresponding to green. We found no evidence for blue‐green (“grue”) confusion. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 206–216, 2016     

A Parametric Methodology in Tuning the Peng-Robinson (PR) Equation of State for Gas Condensate Systems

A tuned equation of state (EOS) is used in reservoir engineering for the evaluation of gas and condensate reserves, desired production methods, and facilities for field development. Publications show that the two most widely used sets of parameters from the EOS that are tuned are the binary interaction coefficient (BIC) with the critical properties and acentric factor or BIC and the constants called the omegas (Ωs). A volume shift parameter (VSP) can also be used in cubic EOS as a tuning parameter to correct for the prediction of liquid density. However, the open literature does not demonstrate if the VSP could be used with one or both parameter sets. In this study, the Peng-Robinson EOS was tuned and tested to predict constant volume depletion (CVD) data for six gas condensate samples. The two sets of tuning parameters were used with and without the VSP. Our parametric study demonstrated that the VSP should not be applied with the Ωs when tuning the Peng-Robinson EOS. With weight factors of 1 for liquid volume and 10 for gas compressibility, without the VSP, the Ωs give better prediction of CVD data than the critical properties and acentric factor even with the VSP included. This tuning technique with one regression step showed consistency in tuning the Peng-Robinson EOS with the Ωs and could be used for simulation studies of gas condensate systems.     

The ANFIS-PSO strategy as a novel method to predict interfacial tension of hydrocarbons and brine

The interfacial tension of hydrocarbons and brine is known as one of the important parameters which are measured in petroleum and petrochemical industries for example the interfacial tension has straight effect on trapping of oil in a reservoir. In the present work the Adaptive neuro-fuzzy inference system (ANFIS) algorithm was used as a novel approach for estimation of interfacial tension between hydrocarbons and brine as function of pressure, temperature, carbon number of hydrocarbon and ionic strength of brine then the particle swarm optimization (PSO) was used to optimize the predicting model parameters.in order to better evaluation of performance of predicting algorithm the coefficient of determination (R²), average absolute relative deviation (AARD) and root mean squared error (RMSE) were estimated for different steps. The outcomes of this investigation expressed that proposed model has high potential for prediction of interfacial tension between hydrocarbons and brine.