Abstract
Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors' research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players' portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator - MIBEL.

Abstract
Wireless Underground Networks (WUNs) include communications links between buried nodes and between buried and aboveground nodes. WUNs have many applications, such as border surveillance, agriculture monitoring, and infrastructure monitoring. Recent studies have shown that they are feasible and have deployment advantages over wired networks. Yet, so far WUNs evaluations have been done using testbeds only, and a tool enabling simulations on TCP/IP WUNs is lacking. We propose a simulator of TCP/IP wireless underground networks based on ns-3. The simulator was validated against experimental results for 433 MHz and 2.4 GHz frequency bands. The results show its accuracy for most of the communications scenarios.

Abstract
This work addresses an integrated framework for deciding about the supplier selection in processed food supply chains that accounts for tactical production and distribution planning. We are especially concerned with the option of producing with local or mainstream raw materials. The contribution of this paper is two-fold. Firstly, it proposes a new multi-objective two-stage stochastic mixed-integer programming model for the supplier selection that maximizes the profit and minimizes the risk of a low customer service. Secondly, the main complexities of processed food supply chains management are considered: perishability of raw materials and final products, uncertainty at downstream and upstream parameters, and customer willingness to pay. Results indicate that dual sourcing is a strategy to be pursued across several scenarios. The multi-objective approach shows that a small decrease in the expected value of profit results in a significant increase in the customer service. Acknowledging the increase in customers willing to pay for local products is also fundamental.

Abstract

Abstract
A sensing configuration for fluid evaporation monitoring using a suspended-core fiber tip is proposed. Strong differences between the evaporation processes of acetone and isopropyl alcohol were observed, both in terms of the signal's intensity fluctuations and total duration. In each fluid, the main signal variations were due to changes in reflectivity inside a collapsed region of the suspended-core fiber near the spliced interface with a standard single-mode fiber. After further analysis with a wider array of substances, this configuration could, in the future, be used to detect and study the evaporation of different volatile organic compounds. (C) 2014 Optical Society of America

Abstract
Legislation defined to protect domestic and non-domestic customers from long durations of interruptions includes additional requirements to system's reliability-related performance that distribution network operators (DNOs) must consider in planning the operation and maintenance process of power supply systems. DNOs are required to restore the supply to interrupted customers that fall into "unprotected" customer class within a given period of time, otherwise penalties are applied. In order to meet these requirements, comprehensive strategies must be defined based on upfront analyses. Accordingly, this paper proposes a deterministic algorithm for estimating DNOs' risk of experiencing interruptions with durations above imposed targets. Besides the Regulator-defined legislation, security of supply requirements are engaged in the development of the proposed methodology. Failure analysis of network components is used to identify interrupted customers that are grouped into power demand classes such that the duration of interruptions can be addressed following the security of supply requirements. Moreover, the penalty times defined by the Energy Regulator are engaged in the analysis and used as thresholds to quantify the penalty risk that DNOs are exposed to. The proposed methodology is applied to a typical UK distribution system, whose average reliability performance is also considered in the analysis. © 2013 Elsevier Ltd. All rights reserved.