Eduardo Matallanas

Heterogeneous collaborative sensor network for electrical management of an automated house with PV energy.

In this paper we present a heterogeneous collaborative sensor network for electrical management in the residential sector. Improving demand-side management is very important in distributed energy generation applications. Sensing and control are the foundations of the “Smart Grid” which is the future of large-scale energy management. The system presented in this paper has been developed on a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead-acid batteries, controllable appliances and smart metering. Therefore, there is a large number of energy variables to be monitored that allow us to precisely manage the energy performance of the house by means of collaborative sensors. The experimental results, performed on a real house, demonstrate the feasibility of the proposed collaborative system to reduce the consumption of electrical power and to increase energy efficiency.

Effects of Large-scale PV Self-consumption on the Aggregated Consumption☆

Self-consumption is modifying the classical structure of the electrical grids worldwide. This energy supply method allows a distributed energy generation and the possibility of involving citizens in the electrical grid. Many countries have defined or are defining rules regarding self-consumption because of the evidence of its unstoppable growth. From the technical point of view, there are numerous associated advantages to the self-consumption, nevertheless it represents a new challenge in the management and design of the electrical grids. In general, the main generation technology for self-consumption is the PV energy. The PV generators are installed in a facility and their generation can be considered as a reduction on the local consumption or even negative consumption. Therefore, high penetration of PV self-consumption will modify the aggregated consumption shape of the electrical grid. The electrical grid should be able to respond to this new shape by adapting generation, controlling consumption or using storage systems. In this paper, we analyze the effects of high penetration of PV self-consumption on the aggregated consumption of the Spanish electrical grid. For this analysis we use historical solar resource data from different cities of Spain and historical data of the aggregated consumption of the country. The results show that PV self-consumption can smooth the aggregated consumption shape, mainly during summer periods. On the other hand, the PV self-consumption can increase the variability of the aggregated consumption shape for high penetration levels.

Multifrequency-Coupled Oscillators for Distributed Multiagent Coordination

The coordination of multiagent systems in real environments receives considerable attention from research and industry. The design of coordination mechanisms should take into account the nature of the environment where the system is embedded. In this paper, the multiagent system is in an environment that features periodic properties. This environment is approached from a signal processing point of view to extract such properties. The coordination is performed by the proposed multifrequency-coupled oscillators (MuFCO) algorithm. It addresses the coordination of the multiagent system as a distributed collective synchronization mechanism. An operation example of MuFCO algorithm is shown, where it is used to coordinate consumptions in a smart grid. Thanks to the MuFCO algorithm, the multiagent system can be used to smooth the aggregated consumption of an electrical grid in a distributed way.

Variable Threshold Algorithm for Division of Labor Analyzed as a Dynamical System

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

Modeling the shape hierarchy for visually guided grasping

The monkey anterior intraparietal area (AIP) encodes visual information about three-dimensional object shape that is used to shape the hand for grasping. We modeled shape tuning in visual AIP neurons and its relationship with curvature and gradient information from the caudal intraparietal area (CIP). The main goal was to gain insight into the kinds of shape parameterizations that can account for AIP tuning and that are consistent with both the inputs to AIP and the role of AIP in grasping. We first experimented with superquadric shape parameters. We considered superquadrics because they occupy a role in robotics that is similar to AIP, in that superquadric fits are derived from visual input and used for grasp planning. We also experimented with an alternative shape parameterization that was based on an Isomap dimension reduction of spatial derivatives of depth (i.e., distance from the observer to the object surface). We considered an Isomap-based model because its parameters lacked discontinuities between similar shapes. When we matched the dimension of the Isomap to the number of superquadric parameters, the superquadric model fit the AIP data somewhat more closely. However, higher-dimensional Isomaps provided excellent fits. Also, we found that the Isomap parameters could be approximated much more accurately than superquadric parameters by feedforward neural networks with CIP-like inputs. We conclude that Isomaps, or perhaps alternative dimension reductions of visual inputs to AIP, provide a promising model of AIP electrophysiology data. Further work is needed to test whether such shape parameterizations actually provide an effective basis for grasp control.

CPV hybrid system in ISFOC building, first results

PV Off-Grid systems have demonstrated to be a good solution for the electrification of remote areas [1]. A hybrid system is one kind of these systems. The principal characteristic is that it uses PV as the main generator and has a backup power supply, like a diesel generator, for instance, that is used when the CPV generation is not enough to meet demand. To study the use of CPV in these systems, ISFOC has installed a demonstration hybrid system at its headquarters. This hybrid system uses CPV technology as main generator and the utility grid as the backup generator. A group of batteries have been mounted as well to store the remaining energy from the CPV generator when nedeed. The energy flows are managed by a SMA system based on Sunny Island inverters and a Multicluster-Box (figure 1). The Load is the air-conditioning system of the building, as it has a consumption profile higher than the CPV generator and can be controlled by software [2]. The first results of this system, as well as the first chances of improvement, as the need of a bigger CPV generator and a better management of the energy stored in the batteries, are presented in this paper.