Abstract
The IEC 61499 standard proposes an event driven execution model for distributed control applications for which an informal execution semantics is provided. Consequently, run-time implementations are not rigorously described and therefore their behavior relies on the interpretation made by the tool provider. In this paper, as a step towards a formal semantics, we focus on the Execution Control Chart semantics, which is fundamental to the dynamic behavior of Basic Function Block elements. In particular we develop a well-formedness criterion that ensures a finite number of Execution Control Chart transitions for each triggering event. We also describe the first step towards the mechanization of the well-formedness checking algorithm in the Coq proof-assistant so that, ultimately, we are able to show, once and for all, that this algorithm is effectively correct with respect to our proposed execution semantics. The algorithm is extractable from the mechanization in a correct-by-construction way, and can be directly incorporated in certified toolchain for analysis, compilation and execution of IEC 61499 models. As a proof of concept a prototype tool RTFM-4FUN has been developed. It performs well-formedness checks on Basic Function Blocks using the extracted algorithm's code.

Abstract
The solar power penetration in distribution grids is growing fast during the last years, particularly at the low-voltage (LV) level, which introduces new challenges when operating distribution grids. Across the world, distribution system operators (DSO) are developing the smart grid concept, and one key tool for this new paradigm is solar power forecasting. This paper presents a new spatial-temporal forecasting method based on the vector autoregression framework, which combines observations of solar generation collected by smart meters and distribution transformer controllers. The scope is 6-h-ahead forecasts at the residential solar photovoltaic and medium-voltage (MV)/LV substation levels. This framework has been tested in the smart grid pilot of vora, Portugal, and using data from 44 microgeneration units and 10 MV/LV substations. A benchmark comparison was made with the autoregressive forecasting model (AR-univariate model) leading to an improvement on average between 8% and 10%.

Abstract

Abstract
In this paper, a detailed home energy management system structure is developed to determine the optimal day-ahead appliance scheduling of a smart household under hourly pricing and peak power-limiting (hard and soft power limitation)based demand response strategies. All types of controllable assets have been explicitly modeled, including thermostatically controllable (air conditioners and water heaters) and nonthermostatically controllable (washing machines and dishwashers) appliances, together with electric vehicles (EVs). Furthermore, an energy storage system (ESS) and distributed generation at the end-user premises are taken into account. Bidirectional energy flow is also considered through advanced options for EV and ESS operation. Finally, a realistic test-case is presented with a sufficiently reduced time granularity being thoroughly discussed to investigate the effectiveness of the model. Stringent simulation results are provided using data gathered from real appliances and real measurements.

Abstract
A coordinated strategy between wind and reversible hydro units for the mid-term that reduces the imbalance of wind power and improves system efficiency is proposed. A stochastic mixed integer linear model is used, which maximizes the joint profit of wind and hydro energies and Conditional Value at Risk (CVaR), where CVaR is the tool utilized to model risk. The offering strategies studied are: i) separate wind and hydro pumping offers, where the units work separately without a physical connection and ii) single wind and hydro pumping offer with a physical connection between them to store the wind energy for future use. The effects of a coordinated wind-hydro strategy for the mid-term are analyzed, considering CVaR and the future water value. The future water value in the reservoirs is analyzed for a period of two months, hour by hour, in a realistic case study.

Abstract
This letter presents a fiber-optic cavity ring down (CRD) configuration using an added-signal for curvature sensing. An optical time-domain reflectometer was used to send impulses down into the fiber loop cavity, inside of which a long period grating was placed to act as a sensing device. The added-signal was obtained by the sum of several conventional CRD impulses, thus providing an improvement on the curvature sensitivity when compared with the conventional CRD signal processing. A linear response to applied curvature in the range of 2.2-3.6 m(-1) was observed, and a sensitivity of 15.3 mu s/m(-1) was obtained. This result was found to be 20-fold the one obtained for the conventional CRD signal processing. The added-signal increases the optical power but increases as well the ring-down time due to the sum of the several loops that light travels inside the ring. A ring-down time response of 43.3 mu s was attained (versus 23.7 mu s for the conventional CRD signal processing).