In Smart Grid system, the consumers are provided with the opportunity to schedule their home appliances in response to variations in electricity price over time. This paper presents the optimal scheduling of resident ...
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In Smart Grid system, the consumers are provided with the opportunity to schedule their home appliances in response to variations in electricity price over time. This paper presents the optimal scheduling of resident ap-pliances. This optimal scheduling is formulated as an optimization problem and is solved by applying improved Genetic algorithm (GA). In this improved GA, the selection of chromosomes is carried out using entropy method, blended crossover and mutation is performed using correlation coefficient. The simulation is performed for a single resident load profile for a set of appliances using Python programming. The result shows the reduction in the electricity cost to that of the original. The number of iterations taken by the improved Genetic algorithm (GA) is comparatively lesser than the standard GA and the execution time is reduced by 2.76 s. Thus the result proves the effectiveness of the proposed improvisation in Genetic algorithm for optimal load scheduling.
Relative permeability of surfactant-polymer (SP) flooding is determined by an inversion method based on numerical simulation and unsteady-state coreflooding experiment. Compared with the common methods, this method is...
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Relative permeability of surfactant-polymer (SP) flooding is determined by an inversion method based on numerical simulation and unsteady-state coreflooding experiment. Compared with the common methods, this method is more time-saving and simpler than steady-state method, and considers more physicochemical properties (adsorption and diffusion) of SP than unsteady-state method based on Buckley-Leverett theory. It is also more applicable to reservoir engineering than pore-scale simulation. After the reliability is confirmed, the superiority of the method is strongly proved by studying the influence of adsorption and diffusion of SP on relative permeability. Comparing relative permeability with and without effect of adsorption and diffusion of SP, the findings show adsorption and diffusion of SP significantly reduce the average inversion error of relative permeability curve from 11.9 to 3.7 for oil and from 10.7 to 1.8 for water. On this basis, the variations of SP flooding relative permeability under the effect of polymer and surfactant are discussed in turn. In the existing researches, the quantitative characterization of variation of SP-flooding relative permeability curves is limited by curve crossing and endpoint saturation changes. In this work, normalized relative permeability is introduced to eliminate the adverse effect caused by curve crossing and endpoint saturation changes. The findings show that although the rise of aqueous-phase viscosity reduces water relative permeability, it has little effect on normalized water relative permeability. Normalized oil and water relative permeability increase in logistic functions with the decrease of IFT in semi-logarithmic plot. Water relative permeability at residual oil endpoint decreases linearly as aqueous-phase viscosity increases, and increases exponentially as IFT decreases in semi-logarithmic plot. Ultimately, the functional models based on normalized relative permeability and cubic B-spline are built through mu
System Protection Security Assessment is an important task in modern energy grids to ensure system security at all. The assessment system is particularly challenged by multivariate grid structures caused by volatile r...
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System Protection Security Assessment is an important task in modern energy grids to ensure system security at all. The assessment system is particularly challenged by multivariate grid structures caused by volatile renewable infeeds. This paper presents an innovative strategy to evaluate the protection relay coordination of system-wide power grids. A way to calculate the quality of all protection relays based on realistic simulation data and independent of the protection method was sought. The hybrid algorithm consists of two major steps. First, a systematic analysis with various fault simulations is performed and the measurement results of all relays of all simulations are used as database. Subsequently, the use of fuzzy sets allows to express the quality of each relay setting regardless of its type. Specifically developed for the use of an optimization algorithm, finally, a new protection coordination is determined for an adapted version of the IEEE 9 bus grid. The results are validated, discussed and the effectiveness of the methodology compared to conventional setting rules.
The ability to maneuver within the atmosphere during orbital return is a major advantage of high-lift vehicles. For example, a maximum lift/drag ratio of nearly 2 affords the Space Shuttle orbiter a choice of several ...
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The ability to maneuver within the atmosphere during orbital return is a major advantage of high-lift vehicles. For example, a maximum lift/drag ratio of nearly 2 affords the Space Shuttle orbiter a choice of several landing sites. In addition, the Shuttle can be rolled during entry while still maintaining a shallow glide trajectory. This roll maneuver during entry reduces the descent time and, therefore, the total heat input, although the heating rate is increased. One typical measure of maneuvering capability is the maximum lateral range that a vehicle can achieve;the solution to this problem was originally given. Another important maneuver consists of performing turns that change the vehicle's heading. This paper contains a brief analysis of turning maneuvers during gliding flight, including lateral distances traversed, at velocities up to circular satellite speed.
We study several versions of the alternating direction method of multipliers (ADMM) for solving the convex problem of finding the distance between two ellipsoids and the non convex problem of finding the distance betw...
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We study several versions of the alternating direction method of multipliers (ADMM) for solving the convex problem of finding the distance between two ellipsoids and the non convex problem of finding the distance between the boundaries of two ellipsoids. In the convex case we present the ADMM with and without automatic penalty updates and demonstrate via numerical experiments on problems of various dimensions that our methods significantly outperform all other existing methods for finding the distance between ellipsoids. In the nonconvex case we propose a heuristic rule for updating the penalty parameter and a heuristic restarting procedure (a heuristic choice of a new starting for point for the second run of the algorithm). The restarting procedure was verified numerically with the use of a global method based on KKT optimality conditions. The results of numerical experiments on various test problems showed that this procedure always allows one to find a globally optimal solution in the nonconvex case. Furthermore, the numerical experiments also demonstrated that our version of the ADMM significantly outperforms existing methods for finding the distance between the boundaries of ellipsoids on problems of moderate and high dimensions.& nbsp;(c) 2021 Elsevier Inc. All rights reserved.
Implementation of optimization algorithm for test case generation in Model-Based Testing (MBT) for Software Product Line (SPL) has been increasing, due to the demand for optimal test case results with a balanced trade...
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Implementation of optimization algorithm for test case generation in Model-Based Testing (MBT) for Software Product Line (SPL) has been increasing, due to the demand for optimal test case results with a balanced trade-off between cost and effectiveness measure. This paper proposed a hyper-heuristic test cases generation approach in MBT for SPL called Improvement Selection Rules-Modified Choice Function (ISR-MCF). ISR-MCF is implemented with three search operators which are Non-Dominated Sorting Genetic algorithm II with low-level heuristic (NSGA-II-LLH), Strength Pareto Evolutionary with Low-Level Heuristic (SPEA 2-LLH) and Particle Swarm optimization with Low-Level Heuristic (PSO-LLH). The approach was evaluated with a test model and the result shows that the proposed ISR-MCF with NSGA-II-LLH outperforms other existing rules for minimization measure (size of a test suite and execution time and maximization measure (coverage criteria).
This paper analyzes transfer trajectories from Earth to Mars with ballistic capture. To begin with, the dynamics of capture orbits on Mars is studied in the framework of a restricted three-body problem. Subsequently, ...
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This paper analyzes transfer trajectories from Earth to Mars with ballistic capture. To begin with, the dynamics of capture orbits on Mars is studied in the framework of a restricted three-body problem. Subsequently, an algorithm is developed to find the weak-stability-boundary trajectories from Earth to Mars in high-fidelity force model taking into account the launch vehicle's payload capabilities. This algorithm was able to find a number of capture trajectories to Mars for all the cases considered in the study.
A microstrip array antenna with low sidelobe level (SLL) for X-band marine radar is proposed. The antenna is composed of a 32-element patch array and a three-layer near-zero-index metamaterial (NZIM). The IABC-Kmeans ...
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A microstrip array antenna with low sidelobe level (SLL) for X-band marine radar is proposed. The antenna is composed of a 32-element patch array and a three-layer near-zero-index metamaterial (NZIM). The IABC-Kmeans algorithm, which combines the improved artificial bee colony algorithm and K-means clustering algorithm, is used to optimize the current amplitude of the array elements to obtain a lower SLL. The NZIM is loaded in front of the array antenna to reduce the beamwidth of the E-plane. The antenna is designed and fabricated. The measurement results show that the gain of the antenna at the center frequency is 22.7 dBi, the SLLs of H-plane and E-plane are -30.66 dB and - 26.78 dB respectively, and the half-power beamwidth of H-plane is 5.9 degrees. Compared with the previous similar antenna structures, the antenna has lower SLL under the premise of narrow beam and high gain, which is very suitable for X-band marine radar of small and medium fishing vessels.
In this paper, a novel compact wideband and high-gain antenna based on metasurface is proposed. The antenna is an octagon with a side length of 32.3 mm and a height of 5.6 mm. The metasurface consists of two stacking ...
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In this paper, a novel compact wideband and high-gain antenna based on metasurface is proposed. The antenna is an octagon with a side length of 32.3 mm and a height of 5.6 mm. The metasurface consists of two stacking layers, and both layers contain a 4x4 copper patch array. The antenna is excited by an aperture coupled structure made of an anomalous microstrip line and a narrow slot etched in the ground plane. Genetic algorithm (GA) is adopted to optimize all the parameters and obtain the valid performance of the metasurface antenna. Moreover, the antenna is modified by introducing nonuniform patch. Modification leads to varying degrees gain enhancement, and the peak is approximately 1.5 dB at 6.1GHz. The impedance bandwidth of the proposed antenna is 54.9%, ranging from 4.48-7.87 GHz. A prototype of the antenna is fabricated, and the measured results verify the design.
As a novel swarm intelligence optimization algorithm, cuckoo search (CS), has been successfully applied to solve various optimization problems. Despite its simplicity and efficiency, the CS is easy to suffer from the ...
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As a novel swarm intelligence optimization algorithm, cuckoo search (CS), has been successfully applied to solve various optimization problems. Despite its simplicity and efficiency, the CS is easy to suffer from the premature convergence and fall into local optimum. Although a lot of research has been done on the shortage of CS, learning mechanism has not been used to achieve the balance between exploitation and exploration. Based on this, a differential CS extension with balanced learning namely Cuckoo search algorithm with balanced-learning (O-BLM-CS) is proposed. Two sets, the better fitness set (FSL) and the better diversity set (DSL), are produced in the iterative process. Two excellent individuals are selected from two sets to participate in search process. The search ability is improved by learning their beneficial behaviors. The FSL and DSL learning factors are adaptively adjusted according to the individual at each generation, which improve the global search ability and search accuracy of the algorithm and effectively balance the contradiction between exploitation and exploration. The performance of O-BLM-CS algorithm is evaluated through eighteen benchmark functions with different characteristics and the logistics distribution center location problem. The results show that O-BLM-CS algorithm can achieve better balance between exploitation and exploration than other improved CS algorithms. It has strong competitiveness in solving both continuous and discrete optimization problems. (C) 2021 The Authors. Published by Atlantis Press B.V.
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