An Evaluation of Non-Stochastic Lattice Structures Fabricated Via Electron Beam Melting

Metal foam structures have many applications and can be used as structural supports, heat exchangers, shock absorbers, and implant materials. Stochastic metal foams having different cell sizes and densities have been commercially available for a number of years. This paper addresses a different type of foams which are known as non-stochastic foams, or lattice structures. These foams have a well defined repeating unit cell structure rather than the random cell structure in commercially available stochastic foams. The paper reports on preliminary research on the fabrication of non-stochastic Ti-6Al-4V alloy foams using the Electron Beam Melting process. Behavior of the structures in compression, bending, and low cycle repeating load tests are discussed, and recommendations about cell geometry and processing conditions are made.Mechanical Engineerin

A Guide to Solar Power Forecasting using ARMA Models

We describe a simple and succinct methodology to develop hourly auto-regressive moving average (ARMA) models to forecast power output from a photovoltaic solar generator. We illustrate how to build an ARMA model, to use statistical tests to validate it, and construct hourly samples. The resulting model inherits nice properties for embedding it into more sophisticated operation and planning models, while at the same time showing relatively good accuracy. Additionally, it represents a good forecasting tool for sample generation for stochastic energy optimization models

Efficient Decentralized Economic Dispatch for Microgrids with Wind Power Integration

Decentralized energy management is of paramount importance in smart microgrids with renewables for various reasons including environmental friendliness, reduced communication overhead, and resilience to failures. In this context, the present work deals with distributed economic dispatch and demand response initiatives for grid-connected microgrids with high-penetration of wind power. To cope with the challenge of the wind's intrinsically stochastic availability, a novel energy planning approach involving the actual wind energy as well as the energy traded with the main grid, is introduced. A stochastic optimization problem is formulated to minimize the microgrid net cost, which includes conventional generation cost as well as the expected transaction cost incurred by wind uncertainty. To bypass the prohibitively high-dimensional integration involved, an efficient sample average approximation method is utilized to obtain a solver with guaranteed convergence. Leveraging the special infrastructure of the microgrid, a decentralized algorithm is further developed via the alternating direction method of multipliers. Case studies are tested to corroborate the merits of the novel approaches.Comment: To appear in IEEE GreenTech 2014. Submitted Sept. 2013; accepted Dec. 201