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
Distribution grids currently face news paradigms where Power Quality (PQ) has become one of the most important aspects for distribution system operators (DSO) and consumers. To ensure a PQ within the limits defined by international standards, there is a permanent need to monitor all parameters associated with the distributed voltage by the grid. This task is carried out using the installation of Power Quality Monitors (PQM) at strategic points of the grid. The main aim of this paper is to define a methodology to optimize the best location for the PQM installation. To achieve this target the Monitor Reach Area (MRA) matrix is calculated and an Integer Linear Programming (ILP) optimization model was used to find the best solution. Two case studies were carried out, in which residual voltage values were observed when three-phase short circuits are applied to all nodes. The results obtained show the good effectiveness of the developed method, presenting solutions that allow the total monitoring of the studied networks, using the smallest possible number of PQMs. In this way, it is possible for the DSO to keep the network monitored in real-time with huge efficiency gains. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

Abstract
Currently, there has been a great development of the wind energy market, which is accompanied by an increase in the number of wind farms at sea, the offshore wind farms. Therefore, it is crucial to ensure that efficiency in energy production is maximum and that the levelized cost of energy (LCOE) is minimal. In this paper, a mixed-integer linear programming model (MILP) is proposed to find the best wind farm layout taking into account the wake effect in order to maximize energy production. The design of an offshore wind farm located at the North Sea is considered as a case study, contemplating three situations regarding the number of wind turbines to be installed and to determine the best positioning of them in order to maximize energy production, taking into account the wake effect and the lowest LCOE. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.