Abstract
Among conventional generation technologies in Spain, Combined Cycle Gas Turbines (CCGT) is the one that has experienced the largest development over the first decade of the 21st century. However, despite its promising future, multiple factors (such as the renewable generation increase, demand decline, adverse regulatory policies, etc.) have compromised their competitive position, reducing their capacity factor and undermining their financial viability. Because of those issues, electricity companies are giving up on new CCGTs investments, or even considering closing or mothballing some of their recently built plants. However, many still claim for the necessity of maintaining flexible backup technologies to cope with the variability of renewable energies, as a transition technology until energy storage or other future technologies emerge. This paper makes a profitability analysis of CCGTs in the Spanish electric power sector under different scenarios of RES penetration, carbon plants decommissioning, CO2 emission costs and EV penetration.

Abstract
European energy strategy towards decarbonization, and its practical implementations in the different EU countries, will imply a continuous increase of variable (non-dispatchable) renewable energy (VRE), like wind and solar PV generation. This increasing VRE along with the progressive closing of current greenhouse gas (GHG) emitting plants, will decrease the net demand (inflexible demand minus non-dispatchable generation), reducing the amount of dispatchable generation needed to face both low VRE periods and larger net demand ramps. These problems need to be assessed to anticipate possible mismatches between net demand values and ramps, and the available resources with generation and ramping capabilities, so that the security and quality of supply is guaranteed. In case of expected risk, regulatory mechanisms, such as new market clearing rules or incentives to new flexibility sources or to new generation and storage technologies, could be required. This paper looks at the possible evolution of the Portuguese power system focusing on the net demand ramp problem. The historical and expected evolution of the hourly ramps of the net demand are analyzed considering different scenarios of high wind and solar PV penetration, according to different degrees of convergence to the EU energy strategic objectives.

Abstract
This paper aims to model collaborative behaviours related to distributed generation investments in a residential neighbourhood, by means of Cooperative Game Theory (CGT). The main objective is to analyse the economic impact of the installation of photovoltaic solar panels and batteries, and the assessment of the potential energy savings due to the cooperation among residential households. In this regard, both the purchase of needed energy from the grid and the sale of the spare energy from the households' self-generation to the grid are considered. The comparison between cooperative and non-cooperative behaviours in the investments and energy management decisions is analysed based on the Shapley value, a cost sharing method from CGT, concluding that cooperation among prosumers to share energy in a residential energy community is in general more efficient than prosumers making individual decisions.

Abstract
Many Generation Expansion Problems (GEP) models have been proposed in the literature based on agent-based equilibria or cost-minimization, integrated in bilevel or single-level models. In the simplest (and unrealistic) single-level cost minimization GEP with only the balance constraint, it can be proved that optimal generation investments are recovered through the system marginal cost, meaning that the Net Present Value (NPV) is 0. However, in more complex representations with additional constraints (such as technical or minimum capacity system constraints) non-profitable investments might occur, i.e., their NPV can go below 0. The aim of this work is to provide insights on how introducing complexity into GEP models affects the investments with and without imposing positive NPV as new constraints. The non-linearities in the NPV formulation are solved with a novel iterative algorithm. The main conclusion from the case studies is that the cost minimization GEP model forcing positive NPV can help to better represent the behavior of energy market players and simulate oligopolistic energy markets without explicitly representing profit maximization.

Abstract
The development of small-scale power generation units based on biomass gasification is an effective mean to meet the growth interest of deployment of local power generation exploiting endogenous renewable energy sources. However, significant research and development activities are required towards the deployment of cost-effective solutions suitable to be used in several applications and with different biomass feedstock. For this purpose, a flexible experimental setup is required to be developed. This paper proposes a critical review of the current state of the art of the available technologies suitable for small-scale power generation using biomass gasification. The main guidelines to develop cost-effective solutions are identified and the conceptual framework of the experimental setup is proposed. Also, the operational specifications are presented.

Abstract
This paper presents a hybrid optimization model based on the metaheuristic Evolutionary Particle Swarm Optimization (EPSO) and Linear Programming for solving the problems of sizing, location and network interface technology selection of battery energy storage system (BESS). The batteries are integrated in a distribution network that has dispersed photovoltaic (PV) generation. Thus, a stochastic scenario generation model is also proposed for creating a database for the PV generation, load and energy prices curves considering historical data. The proposed approach is applied with success to the CIGRE MV benchmark network in the European configuration. Several tests were carried out in order to evaluate the EPSO approach for planning and operate BESS into the modern distribution networks. Experimental results indicate that dispersed solutions to locate the batteries throughout of the network were privileged over concentrated solutions.