Abstract
Despite the fact that reserves still have a small impact on the final electricity price, the rapid irruption of renewable and interruptible technologies has put in the spotlight the value of these services. It seems therefore important to rely on market models able to output realistic energy and reserve prices under imperfect competition. However, few are the authors that have modeled strategic behavior in both commodities. This paper presents an hourly multi-period oligopolistic model for energy and reserve markets, with units' commitment decisions and hydro-coordination, based on the conjectural supply function equilibrium. Its outputs have been compared with real Spanish data from the first weeks of 2011 with satisfactory results. © 2015 IEEE.

Abstract
Cross-border energy markets are becoming more relevant and line congestions may cause significant modifications in their underlined bidding strategies, increasing the market power. This environment requires the development of new tools to measure biased behaviors, and also to try to mitigate them. The related literature makes use of techniques to simulate the bidding strategies, mostly based in optimization models, with or without equilibrium constraints, or mixed complementary problems, and embedded in ad-hoc iterative procedures. This paper presents a model for a two areas system, assuming a conjectural equilibrium. A Mixed Integer Programming method has been implemented to solve the equilibrium conditions, where a binary variable is used to represent the line's power flow status (congested or not) between both two areas. Instead of an ad-hoc algorithm, the Branch and Bound algorithm is used for the resolution, which can assure convergence in specific situations where previous algorithms may diverge. © 2014 IEEE.

Abstract
This paper analyzes the optimal planning and operation of aggregated distributed energy resources (DER) with participation in the electricity market. Aggregators manage their portfolio of resources in order to obtain the maximum benefit from the grid, while participating in the day-ahead wholesale electricity market. The goal of this paper is to propose a model for aggregated DER systems planning, considering its participation in the electricity market and its impact on the market price. The results are the optimal planning and management of DER systems, and the appropriate energy transactions for the aggregator in the wholesale day-ahead market according to the size of its aggregated resources. A price-maker approach based on representing the market competitors with residual demand curves is followed, and the impact on the price is assessed to help in the decision of using price-maker or price-taker approaches depending on the size of the aggregated resources. A deterministic programming problem with two case studies (the average scenario and the most likely scenario from the stochastic ones), and a stochastic one with a case study to account for the market uncertainty are described. For both models, market scenarios have been built from historical data of the Spanish system. The results suggest that when the aggregated resources have enough size to follow a price-maker approach and the uncertainty of the markets is considered in the planning process, the DER systems can achieve up to 50% extra economic benefits, depending on the market share, compared with a non aggregated business-as-usual approach (not implementing DER systems).

Abstract
Net Present Value (NPV), Weighted Average Cost of Capital (WACC), Internal Rate of Return (IRR), and Total-Life Cost of Capital (TLCC) are economic concepts widely used in capital budgeting to measure and compare the profitability of investments. More specifically, in the electricity sector these measures, with the Levelized Cost of Energy (LCOE), are very often used to assess investments in generation assets. At the same time, electricity generation models based on mathematical programming and game theory have also been developed to determine optimal expansion plans of the generation capacity for long-term horizons. Though these two techniques have both been applied in the literature to assess generation investments in the electricity sector, taking into account, among others, investment, maintenance and operation costs, their mathematical relationships have been rarely reported or even understood. Here we provide some insight on the mathematical links existing between both approaches. © 2015 IEEE.

Abstract
The technical and economic importance of electricity ancillary services, responsible for guaranteeing the reliability and security of the power systems, is growing due to the continuous penetration of intermittent technologies. Indeed, changes in the net demand are forcing more expensive thermal generation to provide reserves while reducing their energy production. Therefore generation companies' are more and more concerned with reserve markets and their impact on the electricity market forecasting models. This paper analyses historical data from the Spanish electricity market to better understand and forecast secondary reserve requirements and real-time secondary reserve usage. It focuses on the relationship between secondary reserve requirements by the System Operator and the secondary reserve finally cleared, the long term evolution of secondary reserve requirements with respect to the intermittent generation growing, their annual and daily seasonalities, the real-time secondary reserve usage and its annual and daily seasonalities, and some additional hints for the requirements forecasting. Several interesting and not always intuitive conclusions are drawn from the analyzed data. © 2014 IEEE.

Abstract
The increasing penetration of Intermittent Generation (IG) is being accompanied by the revision of the needs of traditional regulation reserves, as well as the discussion of new flexibility products for system balancing. In the context of electricity generation models, it is of high relevance to adequately represent, not only the energy, but also the reserve dispatch constraints, by providing the models with the expected secondary reserve requirements (SRR), so as to output more realistic energy and reserve schedules and prices. This paper analyses the SRR published by the Spanish System Operator and uses several forecasting tools for determining its main explanatory variables. Results confirm that the SRR have remained almost constant during the years of significant IG growth (and even slightly decreasing in the most recent years), and that the best SRR estimation models found use the demand and its inter-hour variations as the main explanatory variables, but not wind productions as could be expected. © 2017 IEEE.