Abstract
While in the past the installation of distributed generation systems was oftentimes motivated by attractive feed-in tariffs, many consumers now install such systems to increase their self-sufficiency in order to avoid rising electricity cost. However, due to the intermittency of photovoltaic systems and the dependency of cogeneration units on the thermal demand, there remains a significant mismatch between local generation and demand. Electrical storage devices can align generation and demand, minimizing the mentioned gap and hence the amount of energy that needs to be taken from the grid. This paper describes a model to determine the optimal dispatch of such a system, taking the thermal system into account in order to account for the dependency of cogeneration units. A mixed integer program is presented, which identifies the cost minimizing operation schedule. This model is tested using a case study considering realistic values taken from the German case.

Abstract
This paper describes an enhanced model for the Short Term Hydro Scheduling Problem, HSP, that includes the impact of operation decisions on the market prices and the possibility of adjusting the tailwater level. Additionally, the efficiency of hydraulic turbines is treated as a variable dependent on the discharged flows. The developed solution algorithm uses an iterative approach that solves in each iteration a linearized HSP problem using the linprog function of the MATLAB (R) Optimization Toolbox. In each iteration, the value of the head to use in the next iteration is updated. The paper reports results from a realistic Case Study based on the cascade of 9 hydro stations (4 of them with pumping) installed in the Portuguese section of the Douro River.

Abstract
A vital element in making a sustainable world is correctly managing the energy in the domestic sector. Thus, this sector evidently stands as a key one for to be addressed in terms of climate change goals. Increasingly, people are aware of electricity savings by turning off the equipment that is not been used, or connect electrical loads just outside the on-peak hours. However, these few efforts are not enough to reduce the global energy consumption, which is increasing. Much of the reduction was due to technological improvements, however with the advancing of the years new types of control arise. Domestic appliances with the purpose of heating and cooling rely on thermostatic regulation technique. The study in this paper is focused on the subject of an alternative power management control for home appliances that require thermal regulation. In this paper a Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat with the aim of minimizing the cooling energy consumption through the minimization of the energy cost while satisfying the adequate temperature range for the human comfort. In addition, the Model Predictive Control problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. For this purpose, the typical consumption of a 24 h period of a summer day was simulated a three-level tariff scheme was used. The new contribution of the proposal is a modulation scheme of a two-level Model Predictive Control's control signal as an interface block between the Model Predictive Control output and the domestic appliance that functions as a two-state power switch, thus reducing the Model Predictive Control implementation costs in home appliances with thermal regulation requirements.

Abstract
The DC/DC boost converter is described as a time variant system. State-Space is one of the methods used to approach a time variant system to an invariant time linear system. The present document focuses on a comparative approach of output voltage regulation and system stability and performance. For this document, there were made MatLab tests of PI and PD controllers, with and without fuzzy control.

Abstract
This paper describes a new current control method that enhances the dynamic performance of a singlephase bidirectional AC-DC battery charger to provide a high-frequency link between the grid and electric vehicle. The single-stage structure and the bidirectional power flow make the matrix converter an attractive solution for electric vehicle (EV) battery charging applications in the context of smart grids. The operating principles and modulation method are analyzed and discussed in detail. Furthermore, a current controller improved with a Smith predictor is proposed to decrease the phase delay in the measurement of the average current in the battery pack. The SP reduces the rise time to around a third and the settling time to half when compared with a PI controller. Simulations and experimental results from a laboratory prototype are shown to verify the feasibility of the proposed control scheme.

Abstract
A distinctive characteristic of a Microgrid (MG) system is related to the ability of operating autonomously. However, the stability of the system relies in storage and generation availability, providing frequency and voltage regulation. Considering the deployment of distributed storage units in the Low Voltage network and of smart metering infrastructures, this paper presents an online tool for promoting an effective coordination of MG flexible resources in order ensure a secure autonomous operation and maximize the time that the MG is able to operate islanded from the main grid. The tool determines a priori an emergency operation plan for the next hours, based on load and microgeneration forecasting. The limited energy capacity of the distributed storage units participating in MG control is also considered.