Abstract
It is expected that demand response might provide soon ancillary services to the power system. This could be done, for example, by managing the use of Electric Vehicles (EV) batteries, or the production of flexible energy commodities such as hydrogen (H-2), that can be used for fuel cell vehicles (H2EV) or in industrial processes. This paper analyses the impact of a transition to H2EV as an alternative to EV for passengers' cars on a Spanish-like power sector. A simple H-2 demand estimation is developed and provided to CEVESA, an operation and expansion model for the Iberian Power System Electricity Market (MIBEL). For this study, CEVESA was extended to include the investments and operation decisions of H-2 production. Simulations were performed to determine the optimal evolution of the H-2 production capacity and of the electricity generation mix, considering scenarios with different shares of EV and H2EV. The impact of H2EV vs EV mobility is assessed based on the recent Spanish National Plan for Energy and Climate (NECP) as the base case scenario. Results show that, even if H2EV mobility alternative is still more costly than EV, H-2 production could provide a significant flexibility to the system that should also be appraised. Indeed, H2EV mobility could become a feasible and complementary alternative to decarbonize mobility by powering H-2 production with the renewable generation surplus. This, together with the on-going learning process of this technology that will decrease its production costs and increase its efficiency in the coming years, could boost, even more, the development of the H-2 economy.

Abstract
This work proposes a mathematical linear programming model that addresses the food provisioning problem of the food bank of Madrid. It aims to determine the most appropriate weekly decisions to meet the macro-nutritional requirements of the beneficiaries of this social service, by minimizing the total cost considering third-party donations. The model has been applied to a realistic case study considering a sociological structure of beneficiaries categorized by age and gender and representing the first decile of incomes of the Spanish population. The demand of macronutrients is satisfied by means of nine different groups of food, used to provide some level of variability in the consumption patterns of the beneficiaries. The results provide insight on cost-cutting opportunities related to centralizing the decision-making process, indicating a 10% reduction both in provisioning costs and food quantities. This suggests that the proposed model might serve as a tool for designing new strategies for the provisioning or evaluation of economic and social support policies for the food bank of Madrid.

Abstract
In order to avoid voltage problems derived from the connection of large amounts of renewable-based generation to the electrical distribution system, new advanced tools need to be developed that are able to exploit the presence of Distributed Energy Resources (DER). This paper describes the approach proposed for a predictive voltage control algorithm to be used in Low Voltage (LV) distribution networks in order to make use of available flexibilities from domestic consumers via their Home Energy Management System (HEMS) and more traditional resources from the Distribution System Operator (DSO), such as transformers with On-Load Tap Changer (OLTC) and storage devices. The proposed algorithm-the Low Voltage Control (LVC)-is detailed in this paper. The algorithm was tested through simulation using a real Portuguese LV network and real consumption and generation data, in order to evaluate its performance in preparation for a field-trial validation in a Portuguese smart grids pilot.

Abstract
Glycosomes of trypanosomatids are peroxisome-like organelles comprising unique metabolic features, among which the lack of the hallmark peroxisomal enzyme catalase. The absence of this highly efficient peroxidase from glycosomes is presumably compensated by other antioxidants, peroxidases of the peroxiredoxin (PRX) family being the most promising candidates for this function. Here, we follow on this premise and investigate the product of a Leishmania infantum gene coding for a putative glycosomal PRX (LigPRX). First, we demonstrate that LigPRX localizes to glycosomes, resorting to indirect immunofluorescence analysis. Second, we prove that purified recombinant LigPRX is an active peroxidase in vitro. Third, we generate viable LigPRX-depleted L. infantum promastigotes by classical homologous recombination. Surprisingly, phenotypic analysis of these knockout parasites revealed that promastigote survival, replication, and protection from oxidative and nitrosative insults can proceed normally in the absence of LigPRX. Noticeably, we also witness that LigPRX-depleted parasites can infect and thrive in mice to the same extent as wild type parasites. Overall, by disclosing the dispensable character of the glycosomal peroxiredoxin in L. infantum, this work excludes this enzyme from being a key component of the glycosomal hydroperoxide metabolism and contemplates alternative players for this function.

Abstract
This study proposes a stochastic optimisation programming for scheduling a microgrid (MG) considering multiple energy devices and the uncertain nature of renewable energy resources and parking lot-based electric vehicles (EVs). Both thermal and electrical features of the multi-energy system are modelled by considering combined heat and power generation, thermal energy storage, and auxiliary boilers. Also, price-based and incentive-based demand response (DR) programs are modelled in the proposed multi-energy MG to manage a commercial complex including hospital, supermarket, strip mall, hotel and offices. Moreover, a linearised AC power flow is utilised to model the distribution system, including EVs. The feasibility of the proposed model is studied on a system based on real data of a commercial complex, and the integration of DR and EVs with multiple energy devices in an MG is investigated. The numerical studies show the high impact of EVs on the operation of the multi-energy MGs.

Abstract
Energy arbitrage have monetary benefits for privately owned battery energy storage systems, such as the battery of an electric vehicle or residential batteries. However, the life cycle and degradation cost of the battery storage should be taken into consideration and can decrease obtained income in the long-term. This paper proposes an optimization framework to derive optimal bidding and offering curves for lead-acid battery storage participate in a stepwise energy market. The objective is to maximize the profit comes from participating in energy arbitrage action, while the life cycle of the battery is considered by objective function and constraints. Due to the small capacity of the considered storage unit, it can be assumed that this unit is a pricetaker participant, which its actions cannot influence the market prices. Hence, the energy prices are modeled as uncertain parameters using stochastic programming approach. The second order stochastic dominance constraints are as risk management method.