Abstract
The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Abstract
The provision of reserves in power systems is of great importance in what concerns keeping an adequate and acceptable level of security and reliability. This need for reserves and the way they are defined and dispatched gain increasing importance in the present and future context of smart grids and electricity markets due to their inherent competitive environment. This paper concerns a methodology proposed by the authors, which aims to jointly and optimally dispatch both generation and demand response resources to provide the amounts of reserve required for the system operation. Virtual Power Players are especially important for the aggregation of small size demand response and generation resources. The proposed methodology has been implemented in MASCEM, a multi agent system also developed at the authors’ research center for the simulation of electricity markets.

Abstract
National governments sometimes introduce policies that modify energy markets to achieve other social and political goals. These policies, created with the best of intentions, often have unintended consequences. Here we present a case study of one such policy, the Royal Decree in Spain that mandates the use of the Spanish-Indigenous Coal (IC). © 2013 IEEE.

Abstract
Intermittent technologies are enhancing both the economic and technological value of ancillary services in the electric power system. Some of these services commonly denoted as reserves have been liberalized and are offered in the balancing markets in the European Union countries, or in the regulation markets in the USA. This paper presents a deterministic single-node centralized energy and secondary reserve dispatch that outputs hourly scheduled energies and reserves, and both commodities prices. In this model, units of each generation company are simplified into technologies and sub-technologies for faster performance, but still considering inter temporal constraints such as ramps and responding time for reserves, and unit commitment decisions such as start-up and shut-down costs. Detailed short-term hydro-thermal constraints (topology, efficiency, etc.) have been simplified by means of weekly constraints based on historical data (inflows, installed capacity, productions). The model has been validated by comparing its output prices and productions with the real ones occurred during 2010 in the Spanish market with satisfactory results. Furthermore, a study-case on high penetration of solar generation in the Spanish system reveals strong interactions between the energy and reserve markets and points out the importance of hydro technologies in the system. © 2013 IEEE.

Abstract
It is expected that in the near future the number of Plug-in Electric Vehicles (PEV) could increase significantly due to their low pollution emissions, high fuel economy, and mitigation of security issues related to oil technical and economic management. Many works have dealt with the impact of PEV on the power and distribution grids, and on other particular aspects, but very few perform more general cost benefit analyses of their global impact. This paper does it in two steps. First, a hydro-thermal unit commitment for a full year simulation provides electricity and reserve prices for different charging strategies. Then, the model computes economic estimations for the costs of the charging infrastructure, specific PEV costs and main externalities (emissions, health benefits and energetic dependence). The model is intended to provide meaningful results on the global economic balance of PEV penetration, helping for example in feed-in tariffs, fuel taxes redesign or other regulatory analyses. © 2013 IEEE.

Abstract
The smart city is a sustainable and efficient urban center that provides high quality of life to its inhabitants with an optimal management of its resources, where clean and cost effective energy generation is a key issue. Under this setting, distributed generation can provide an adequate tool to deal with energy reliability and to successfully implement renewable sources; nevertheless, selection and scaling of energy systems, considering location, is not a trivial task. Frequently, the stakeholders analyze only one or two 'popular' generation systems, and then calculate the output and return of investment in a simplified and approximated approach. This practice could lead the stakeholder to an inadequate technology mix. To tackle this problem, this paper reviews and models most common energy sources for distributed generation in a smart city context. Then, a technical economic analysis is developed for 2 cases, a household and a district, considering not only renewable sources but also efficient non-renewable technologies. The results of the numerical analysis help to assess the more adequate generation systems for a given application, energetic demand, and geographical characteristics. A well-developed analysis is essential for a better understanding of the available technologies and their synergies; as a result, the investors can choose the appropriate solutions, maximizing overall benefits. © 2013 IEEE.