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

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

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 Bézier 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