Abstract
Previous studies of market power within a regional system have considered multiple competing generation operators and the role of transmission constraints. However, these studies typically assume simplified structures in which each operator is restricted to a unique node in a transmission constrained network. Real systems typically have operators making decisions for units in several zones at once. Past studies also implicitly treated market power as a static concept for a given set of market rules and network configuration. We demonstrate that market power is dynamic, and can vary significantly with fuel prices and even with large-scale weather patterns. We also demonstrate the impact on region-wide market power of operators that manage units in multiple zones. We use the Electric Reliability Council of Texas (ERCOT) as an illustrative case study, and apply a conjectured supply function equilibrium (CSFE) approach that accounts for transmission constraints. We show that the companies with greater influence on the market price will depend on the relative prices of coal and natural gas. We also show that a weather event, such as a period without any wind, can have a substantial impact on market power.

Abstract
This paper proposes a linear programming problem to find the optimal planning and operation of aggregated distributed energy resources (DER), managed by an aggregator that participates in the day-ahead wholesale electricity market as a price-maker agent. The proposed model analyzes the impact of the size of the aggregated resources and gives the optimal planning and management of DER systems, and the corresponding energy transactions in the wholesale day-ahead market. The results suggest that when the aggregated resources are large enough, DER systems can achieve up to 32% extra economic benefits depending on the market share, compared with a business-as-usual approach (not implementing DER systems). © 2016 IEEE.

Abstract
A smart city is a sustainable and efficient urban centre that provides a high quality of life to its inhabitants through optimal management of its resources. Energy management is one of the most demanding issues within such urban centres owing to the complexity of the energy systems and their vital role. Therefore, significant attention and effort need to be dedicated to this problem. Modelling and simulation are the major tools commonly used to assess the technological and policy impacts of smart solutions, as well as to plan the best ways of shifting from current cities to smarter ones. This paper reviews energy-related work on planning and operation models within the smart city by classifying their scope into five main intervention areas: generation, storage, infrastructure, facilities, and transport. More-complex urban energy models integrating more than one intervention area are also reviewed, outlining their advantages and limitations, existing trends and challenges, and some relevant applications. Lastly, a methodology for developing an improved energy model in the smart-city context is proposed, along with some additional final recommendations.

Abstract
In order to improve their competitive performance, airline companies often adopt as a strategy to establish arrangement between two or more organizations agreeing to cooperate on a substantial level. This strategy is often known as airline alliances. A paradigm to analyze the collective intelligence behavior which emerges from a group, as a strategic alliance, is the flocking behavior. Inspired by the Cucker and Smale algorithm (C-S) we propose a new version of the flocking behavior algorithm applied to airline alliances. Our goal is to understand the link between strategic alliances and flocks. For this new approach, metrics were obtained for the parameters of C-S algorithm, namely position, velocity and influence, where the latter uses cooperative games. Besides, reinforcement learning mechanisms have been explored. Some relevant outputs for airline alliances as the permanence rate and the growth rate were computed for each of the five configurations in analysis.

Abstract

Abstract
The constant growth of wind farms in the Brazilian electric system increases the concerns regarding power quality, especially related to harmonic distortions. At the same time, wind generation also becomes relevant in the context of power system stability, operating as ancillary services. One of the requirements of the system operator is the injection of reactive power by the wind farms to maintain the voltage levels. Considering that the actual studies only considers the operation of the wind generators with unitary power factor, the present work aims to evaluate the harmonic impact of Wind farms operating with reactive power injection on the electric system buses. For this purpose two monitoring campaigns in a wind farm of the CPFL Renováveis were performed with different power factors operating modes in the wind generators. These results were utilized in computational studies to evaluate the impact in voltage distortion at the PCC. The results obtained in this work demonstrated a significant impact on the harmonic current generation and in the voltage harmonic distortion due to the reactive power injection by the wind generators of the wind farm.