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.

Abstract
Distributed generation (DG) represents an important resource to address relevant energy issues, such as reliability and sustainability, in the current and future smart cities. It is expected that distributed generation will gain considerable presence in the following years; however, the selection and sizing of the generation and storage systems is commonly done without an adequate level of detail. This simplified or approximated approach usually results in a suboptimal technology mix with an inadequate type of system and/or scale, which could compromise the economic feasibility of the DG project. To tackle this problem, stakeholders should consider many factors, including geographical characteristics (sun, wind...) energy costs, local regulation, and energetic demand patterns, apart from analysing different technologies. Considering as an example location the city of Madrid, Spain, this paper proposes a linear programming model to evaluate the most common distributed generation technologies, with and without storage systems and under different electricity pricing scenarios. As a result, not only the optimal sizing, but also the optimal operation scheduling of the aforementioned systems are found. Then, an economic feasibility analysis is developed, comparing the different technologies and defining the best option for a given scenario. Furthermore, this study helps to find important milestones, such as battery prices, that could make distributed generation more attractive. © 2013 WIT Press.

Abstract

Abstract
Many transportation environmental life cycle analyses neglect the contribution of the energy supply infrastructures. In alternative light duty vehicle technologies, it has been shown through case studies that this can be a relevant factor. However, no model that can generalise the evaluation of energy and emissions from construction, maintenance and decommissioning of such infrastructure to analyse different scenarios currently exists. A model is proposed, focussing on electricity and on hydrogen supply through centralised steam methane reforming (H-2(a)) and on-site electrolysis (H-2(b)). The model outputs are in gCO(2eq)/MJ and MJ(eq)/MJ of the final energy. Model main inputs are the region's electricity mix, the annual distance driven, supply chain losses and the number of vehicles per station or chargers. The evaluation of the number of vehicles served per each charger/station as a function of annual distance driven is presented. The uncertainty is estimated by using the pedigree matrix, impact uncertainty and literature estimates. The model shows consistency in the results and uncertainty range. Charging policies that minimise the electricity infrastructure burden should incentivise approximately 37% of normal charging. H-2(a) pipeline lifetime should be extended. Efforts in the electrolyser should be undertaken to approximate the ratio of vehicles per station with a conventional one.