Energy harvesting from hydroelectric systems for remote sensors

Hydroelectric systems are well-known for large scale power generation. However, there are virtually no studies on energy harvesting with these systems to produce tens or hundreds of milliwatts. The goal of this work was to study which design parameters from large-scale systems can be applied to small-scale systems. Two types of hydro turbines were evaluated. The first one was a Pelton turbine which is suitable for high heads and low flow rates. The second one was a propeller turbine used for low heads and high flow rates. Several turbine geometries and nozzle diameters were tested for the Pelton system. For the propeller, a three-bladed turbine was tested for different heads and draft tubes. The mechanical power provided by these turbines was measured to evaluate the range of efficiencies of these systems. A small three-phase generator was developed for coupling with the turbines in order to evaluate the generated electric power. Selected turbines were used to test battery charging with hydroelectric systems and a comparison between several efficiencies of the systems was made. Keywords

Graphical constraints: a graphical user interface for constraint problems

A constraint satisfaction problem is a classical artificial intelligence paradigm characterized by a set of variables (each variable with an associated domain of possible values), and a set of constraints that specify relations among subsets of these variables. Solutions are assignments of values to all variables that satisfy all the constraints. Many real world problems may be modelled by means of constraints. The range of problems that can use this representation is very diverse and embraces areas like resource allocation, scheduling, timetabling or vehicle routing. Constraint programming is a form of declarative programming in the sense that instead of specifying a sequence of steps to execute, it relies on properties of the solutions to be found, which are explicitly defined by constraints. The idea of constraint programming is to solve problems by stating constraints which must be satisfied by the solutions. Constraint programming is based on specialized constraint solvers that take advantage of constraints to search for solutions. The success and popularity of complex problem solving tools can be greatly enhanced by the availability of friendly user interfaces. User interfaces cover two fundamental areas: receiving information from the user and communicating it to the system; and getting information from the system and deliver it to the user. Despite its potential impact, adequate user interfaces are uncommon in constraint programming in general. The main goal of this project is to develop a graphical user interface that allows to, intuitively, represent constraint satisfaction problems. The idea is to visually represent the variables of the problem, their domains and the problem constraints and enable the user to interact with an adequate constraint solver to process the constraints and compute the solutions. Moreover, the graphical interface should be capable of configure the solver’s parameters and present solutions in an appealing interactive way. As a proof of concept, the developed application – GraphicalConstraints – focus on continuous constraint programming, which deals with real valued variables and numerical constraints (equations and inequalities). RealPaver, a state-of-the-art solver in continuous domains, was used in the application. The graphical interface supports all stages of constraint processing, from the design of the constraint network to the presentation of the end feasible space solutions as 2D or 3D boxes.