This paper presents a comparative study on the implementation of incentive-based demand response programs in power grid management, comparing results obtained from linear and nonlinear models. The challenges faced by grids balancing supply managing price spikes during peak periods are addressed, proposed as an effective strategy. focus is implementing where load serving entities determine optim...

The main contribution of the present paper is to train efficient neural networks for seismic design of double layer grids subject to multiple-earthquake loading. As the seismic analysis and design of such large scale structures require high computational efforts, employing neural network techniques substantially decreases the computational burden. Square-on-square double layer grids with the va...

Cell-centered and node-centered approaches have been compared for unstructured finite-volume discretization of inviscid fluxes. The grids range from regular grids to irregular grids, including mixed-element grids and grids with random perturbations of nodes. Accuracy, complexity, and convergence rates of defect-correction iterations are studied for eight nominally second-order accurate schemes:...

Generally, such as bio-fuels, wind, solar, small hydropower, marine and geothermal energy, etc. have been defined as new renewable energy. Photovoltaic and wind power generation have been in rapid growth, but they have characteristics of randomness, intermittent, uncontrollable. Although the idea of effective renewable energy use as a means of coping with environmental and resource problems, es...

Background: Grid-tied inverters play an efficient role in the integration of renewable energy resources with utility grids. Motivation: However, interconnection between power converters and grid has been seen to be responsible for various stability issues such as weak grid, under conditions injection becomes a challenging task due continuously varying impedance affecting margins result. Additio...

Due to severe climate change impact on electricity consumption, as well new trends in smart grids (such the use of renewable resources and advent prosumers energy commons), medium-term long-term load forecasting has become a crucial need. Such forecasts are necessary support plans decisions related capacity evaluation centralized decentralized power generation systems, demand response strategie...

Legendre-Gauss-Lobatto (LGL) grids play a pivotal role in nodal spectral methods for the numerical solution of partial differential equations. They not only provide efficient high-order quadrature rules, but give also rise to norm equivalences that could eventually lead to efficient preconditioning techniques in high-order methods. Unfortunately, a serious obstruction to fully exploiting the po...

Over the last few years, several nations around the world have set up Grids to share resources such as computers, data, and instruments to enable collaborative science, engineering, and business applications. These Grids follow a restricted organizational model wherein a Virtual Organization (VO) is created for a specific collaboration and all interactions such as resource sharing are limited t...

The use of overset grids in CFD started more than two decades ago, and has achieved tremendous success in handling complex geometries. In particular, overset grids have the advantage of avoiding grid remeshing when dealing with moving boundary flow problems. Traditionally overset grids were mainly used with structured grids to simplify the grid generation process, because a complex computationa...

Desktop grids are usually equipped with hundreds or thousands of desktops which use the idle cycles of desktop PCs of small enterprises and institutions. From conventional multi -site cluster grids, desktop grids vary markedly in terms of their dynamic nature. In terms of their dynamic nature such grids vary markedly from conventional grids] . This causes the need of new scheduling algorithms ,...