Abstract
Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

Abstract
Several challenges arrive with electrical power restructuring, liberalized electricity markets emerge, aiming to improve the system's efficiency while offering new economic solutions. Privatization and liberalization of previously nationally owned systems are examples of the transformations that have been applied. Microgrids and smart grids emerge and new business models able to cope with new opportunities start being developed. New types of players appear, allowing aggregating a diversity of entities, e. g. generation, storage, electric vehicles, and consumers, Virtual Power Players (VPPs) are a new type of player that allows aggregating a diversity of players to facilitate their participation in the electricity markets. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. The paper proposes a normalization method that supports a clustering methodology for the remuneration and tariffs definition. This model uses a clustering algorithm, applied on normalized load values, the value of the micro production, generated in the bus associated to the same load, was subtracted from the value of the consumption of that load. This calculation is performed in a real smart grid on buses with associated micro production. This allows the creation of sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision making process is found, according to players characteristics.

Abstract
The increasing use and development of renewable energy sources and distributed generation, brought several changes to the power system operation. Electricity markets worldwide are complex and dynamic environments with very particular characteristics, resulting from their restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources. With the eminent implementation of micro grids and smart grids, new business models able to cope with the new opportunities are being developed. Virtual Power Players are a new type of player, which allows aggregating a diversity of entities, e.g. generation, storage, electric vehicles, and consumers, to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players' benefits. This paper proposes a clustering methodology regarding the remuneration and tariff of VPP. It proposes a model to implement fair and strategic remuneration and tariff methodologies, using a clustering algorithm, applied to load values, submitted to different types of normalization process, which creates sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision making process is found, according to the players characteristics. The proposed clustering methodology has been tested in a real distribution network with 30 bus, including residential and commercial consumers, photovoltaic generation and storage units.

Abstract
The smart grids represent a new and attracting challenge for various research areas. The inclusion of information technologies across the entire electrical grid creates new capacities, with impact on the environment, science and technology, economy and lifestyle. Creation of a smart grid provides utilities and their customers a significant improvement in power reliability and services. This paper presents an overview of smart grid technologies focusing on its characteristics, benefits and challenges. Moreover, this paper reviews the reliability impacts of the major smart grid resources such as renewables, demand response and storage. The main differences between a traditional grid and a smart grid, the trends in the evolution of power distribution systems and the highlights of smart grid segments and applications are also presented. Smart Grids represent one of the great challenges at the global level. Under the effect of political and societal pressure due to climate change and pollution concerns, and enabled by availability of new technologies, the electrical power systems are undergoing reconsideration. Including the technology of information in the whole electric grid creates new capabilities with strong impact in the environment, science and technology, but also in the economy and life in general. The term "smart grid" describes the evolution of the electrical grids and reflects a change of paradigm in the electric market organization and management. Some changes are already on the way to be implemented, such as a growth of the renewable fraction of the generating power, some other are envisioned, such as the fully flexible energy routing or the consumer driven distribution. From a global perspective, implementing smart grids at a large scale will definitely improve the services that supply electrical energy in the future. In recent years, electrical grids have been faced with an increasing concentration of distortion loads that generate distortion, causing both current and voltage harmonic distortions. The impact of these loads increases as their power approaches the power capacity of the grid.

Abstract
Nowadays, the power quality has become not only an important competitive factor for industrial users but also a crucial factor in the energy efficiency of the facilities. Seen paradoxically, the increase we have seen in the energy efficiency of the electrical loads, leads to the intensive use of power electronics resulting in a very high injection of harmonics in the distribution networks, thus causing a lack in the power quality leading a significant voltage waveform deformation. An electrical network containing a high harmonic content is synonymous of a low-level quality of the distributed energy, resulting in an increase of losses and low power factors, decreasing the energy efficiency of the installations. This paper presents a model that allows predicting the harmonic content present in an electrical installation, depending on the type of loads. Hence, it will be possible to know several qualitative parameters such as the voltage and current total harmonic distortion (THD), which will help to predict and size the mitigation measures to improve the power quality and energy efficiency of the facilities. © 2019 IEEE.

Abstract
The increasing use of renewable energy sources and distributed generation brought deep changes in power systems, namely with the operation of competitive electricity markets. With the eminent implementation of micro grids and smart grids, new business models able to cope with the new opportunities are being developed. Virtual Power Players are a new type of player, which allows aggregating a diversity of entities, e.g. generation, storage, electric vehicles, and consumers, to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players' benefits. In order to achieve this objective, it is necessary to define tariff structures that benefit or penalize agents according to their behavior. In this paper a method for determining the tariff structures has been proposed, optimized for different load regimes. Daily dynamic tariff structures were defined and proposed, on an hourly basis, 24 hours day-Ahead from the characterization of the typical load profile, the value of the electricity market price and considering the renewable energy production. © 2018 IEEE.