6,836 research outputs found
Quasi-dynamic Load and Battery Sizing and Scheduling for Stand-Alone Solar System Using Mixed-integer Linear Programming
Considering the intermittency of renewable energy systems, a sizing and
scheduling model is proposed for a finite number of static electric loads. The
model objective is to maximize solar energy utilization with and without
storage. For the application of optimal load size selection, the energy
production of a solar photovoltaic is assumed to be consumed by a finite number
of discrete loads in an off-grid system using mixed-integer linear programming.
Additional constraints are battery charge and discharge limitations and minimum
uptime and downtime for each unit. For a certain solar power profile the model
outputs optimal unit size as well as the optimal scheduling for both units and
battery charge and discharge (if applicable). The impact of different solar
power profiles and minimum up and down time constraints on the optimal unit and
battery sizes are studied. The battery size required to achieve full solar
energy utilization decreases with the number of units and with increased
flexibility of the units (shorter on and off-time). A novel formulation is
introduced to model quasi-dynamic units that gradually start and stop and the
quasi-dynamic units increase solar energy utilization. The model can also be
applied to search for the optimal number of units for a given cost function.Comment: 6 pages, 3 figures, accepted at The IEEE Conference on Control
Applications (CCA
Reliability of Dynamic Load Scheduling with Solar Forecast Scenarios
This paper presents and evaluates the performance of an optimal scheduling
algorithm that selects the on/off combinations and timing of a finite set of
dynamic electric loads on the basis of short term predictions of the power
delivery from a photovoltaic source. In the algorithm for optimal scheduling,
each load is modeled with a dynamic power profile that may be different for on
and off switching. Optimal scheduling is achieved by the evaluation of a
user-specified criterion function with possible power constraints. The
scheduling algorithm exploits the use of a moving finite time horizon and the
resulting finite number of scheduling combinations to achieve real-time
computation of the optimal timing and switching of loads. The moving time
horizon in the proposed optimal scheduling algorithm provides an opportunity to
use short term (time moving) predictions of solar power based on advection of
clouds detected in sky images. Advection, persistence, and perfect forecast
scenarios are used as input to the load scheduling algorithm to elucidate the
effect of forecast errors on mis-scheduling. The advection forecast creates
less events where the load demand is greater than the available solar energy,
as compared to persistence. Increasing the decision horizon leads to increasing
error and decreased efficiency of the system, measured as the amount of power
consumed by the aggregate loads normalized by total solar power. For a
standalone system with a real forecast, energy reserves are necessary to
provide the excess energy required by mis-scheduled loads. A method for battery
sizing is proposed for future work.Comment: 6 pager, 4 figures, Syscon 201
Modeling active electrolocation in weakly electric fish
In this paper, we provide a mathematical model for the electrolocation in
weakly electric fishes. We first investigate the forward complex conductivity
problem and derive the approximate boundary conditions on the skin of the fish.
Then we provide a dipole approximation for small targets away from the fish.
Based on this approximation, we obtain a non-iterative location search
algorithm using multi-frequency measurements. We present numerical experiments
to illustrate the performance and the stability of the proposed multi-frequency
location search algorithm. Finally, in the case of disk- and ellipse-shaped
targets, we provide a method to reconstruct separately the conductivity, the
permittivity, and the size of the targets from multi-frequency measurements.Comment: 37 pages, 11 figure
Stochastic approach to inflation II: classicality, coarse-graining and noises
In this work we generalize a previously developed semiclassical approach to
inflation, devoted to the analysis of the effective dynamics of coarse-grained
fields, which are essential to the stochastic approach to inflation. We
consider general non-trivial momentum distributions when defining these fields.
The use of smooth cutoffs in momentum space avoids highly singular quantum
noise correlations and allows us to consider the whole quantum noise sector
when analyzing the conditions for the validity of an effective classical
dynamical description of the coarse-grained field. We show that the weighting
of modes has physical consequences, and thus cannot be considered as a mere
mathematical artifact. In particular we discuss the exponential inflationary
scenario and show that colored noises appear with cutoff dependent amplitudes.Comment: 18 pages, revtex, no figure
Reproduksi Mekanis pada Karya Seni dan Kaitannya dengan Peran Seniman sebagai Produsen
Reproduksi mekanis pada karya seni adalah salah satu hal dasar yang penulis pelajari di studio seni grafis. Latar belakang penulis sebagai pegrafis menumbuhkan ketertarikan untuk menggali berbagai potensi estetik yang ada pada proses reproduksi mekanis sebagai cara untuk memperbanyak jumlah karya seni orisinal. Penulis menemukan kemiripan proses reproduksi mekanis cetak grafis dengan proses kerja sebuah pabrik industri. Peran seniman bagi penulis menjadi mirip dengan peran seorang pekerja manual, yaitu sama-sama sebagai produsen. Hal ini menjadi pondasi atas rasa solidaritas yang dimiliki penulis terhadap kaum pekerja. Penulis ingin menyampaikan melalui karya Tugas Akhir ini sebuah manifestasi atas ideologi yang dimiliki penulis, dengan inspirasi estetik dari bentuk bentuk yang ada pada lingkungan.pekerja di sekitar penulis, serta memanfaatkan potensi multiplikatif yang ada pada proses reproduksi mekanis
Firefly algorithm approach for rational bézier border reconstruction of skin lesions from macroscopic medical images
Image segmentation is a fundamental step for image processing of medical images. One of the most important tasks in this step is border reconstruction, which consists of constructing a border curve separating the organ or tissue of interest from the image background. This problem can be formulated as an optimization problem, where the border curve is computed through data fitting procedures from a collection of data points assumed to lie on the boundary of the object under analysis. However, standard mathematical optimization techniques do not provide satisfactory solutions to this problem. Some recent papers have applied evolutionary computation techniques to tackle this issue. Such works are only focused on the polynomial case, ignoring the more powerful (but also more difficult) case of rational curves. In this paper, we address this problem with rational BĂ©zier curves by applying the firefly algorithm, a popular bio-inspired swarm intelligence technique for optimization. Experimental results on medical images of melanomas show that this method performs well and can be successfully applied to this problem
The Quantum Emergence of Chaos
The dynamical status of isolated quantum systems, partly due to the linearity
of the Schrodinger equation is unclear: Conventional measures fail to detect
chaos in such systems. However, when quantum systems are subjected to
observation -- as all experimental systems must be -- their dynamics is no
longer linear and, in the appropriate limit(s), the evolution of expectation
values, conditioned on the observations, closely approaches the behavior of
classical trajectories. Here we show, by analyzing a specific example, that
microscopic continuously observed quantum systems, even far from any classical
limit, can have a positive Lyapunov exponent, and thus be truly chaotic.Comment: 4 pages, 4 figure
- …