Abstract
There are different clean energy production technologies, including wind energy production. This type of energy, among renewable energies, is one of the least predictable due to the unpredictability of the wind. The wind prediction has been a deeply analysed field since has a considerable share on the green energy production, and the investments on this sector are growing. The efficiency and stability of power production can be increased with a better prediction of the main source of energy, in our case the wind. In this paper, some techniques inspired by Biological Inspired Optimization Techniques applied to wind forecast are compared. The wind forecast is very important to be able to estimate the electric energy production in the wind farms. As you know, the energy balance must be checked in the electrical system at every moment. In this study we are going to analyse different methodologies of wind and power prediction for wind farms to understand the method with best results.

Abstract
Bidirectional electric vehicle supply equipment and charging stations (EVSE) offer new business models and can provide services to the electrical grid. The smart grid lab in Vienna gives unique testing possibilities of future smart grids, as different type of electrical equipment can be operated at a reconstructed, well-known distribution grid. In this work the harmonic and supraharmonic emissions of a bidirectional EVSE are measured according to IEC61000-4-7 and IEC61000-4-30 Ed3 standard as well as the high-frequency grid impedance. In addition, the efficiency and the power factor are determined at various operating points. Although THDi at nominal power (10 kW) is very low and the efficiency and power factor is very high, at low power levels the opposite situation arise. Supraharmonic emissions remain stable independent of the charging/discharging power, and both wideband and narrowband emissions occur. The additional capacitance when connecting the EVSE impacts the high-frequency grid impedance substantially and generates resonance points.

Abstract
[No abstract available]

Abstract
This paper proposes a decision support model to define electricity consumers' remuneration structures when providing consumption flexibility, optimized for different load regimes. The proposed model addresses the remuneration of consumers when participating in demand response programs, benefiting or penalizing those who adjust their consumption when needed. The model defines dynamic remuneration values with different natures for the aggregator (e.g. flexibility aggregator or curtailment service provider) and for the consumer. The preferences and perspective of both are considered, by incorporating variables that represent the energy price, the energy production and the flexibility of consumers. The validation is performed using real data from the Iberian market, and results enable to conclude that the proposed model adapts the remuneration values in a way that it is increased according to the consumers' elastic, while being reduced when the generation is higher. Consequently, the model boosts the active consumer participation when flexibility is required, while reaching a solution that represents an acceptable g tradeoff between the aggregators and the consumers. (C) 2022 The Authors. Published by Elsevier Ltd.

Abstract
The increase in the world's population combined with the development of new economies has led to a large scale increase in the demand for energy resources. New technologies have emerged that allow for the maintenance of the energy supply. Renewable sources and energy storage systems (ESS) are emerging as a crucial option for the development of Smart Grids. Using a Mixed Integer Linear Programming (MILP) optimization model, the effects of renewable production sources and storage systems on an electrical grid were studied, in order to maximize the profit of a Virtual Power Plant (VPP). The obtained results allowed us to verify the efficiency of the proposed method. The placement of renewable producers and the ESS, as well as the management optimization of the purchase and transfer process of the stored energy definitely increased the profit of VPP. The use of these technologies also improves the voltage profile and decreased the active power losses by 84% along with the network.

Abstract
Nowadays, power distribution systems face some challenges related to power losses minimization and voltage stability improvement along the networks. These challenges can also be a big opportunity to develop smarter and more efficient distribution networks, ensuring the continuity of service and the power quality supplied to consumers. At the same time, there are several international standards that regulate the power quality levels required for distribution networks.This paper addresses deeply these issues and provide a solution to solve both of these problems using Distributed Generators (DG) on optimal locations of the grid. The proposed method will analyze the injection of both real and reactive power in a regulated IEEE-69 bus system. In the first stage, the voltage and loss sensitivity of the load flow analysis is calculated using a MatLab algorithm. In a second stage, the methodology uses the voltage stability index (VSI) to obtain the optimal location of the DGs to ensure the best results of both, power loss and voltage stability for the grid. The obtained results show the good effectiveness of the proposed method.