Abstract
This paper proposes an energy community management system for local energy sharing with grid flexibility services to solve the potential grid constraints of the local distribution network. A three-stage model is proposed. Stage 1 is the individual minimization of the energy bill of each prosumer by optimizing the schedules of its battery. The second stage optimizes the energy bill of the energy community by sharing internally the prosumers energy surplus and re-dispatching their batteries, while guaranteeing that each new individual prosumer energy bill is always equal or less than its stage 1 bill. The third stage is performed by the DSO to solve the grid constraints by re-dispatching the batteries, curtailing local generation or reducing consumption. Stage 3 minimizes the impact on stage 2 by minimizing the loss of profit or utility of every prosumer which is compensated accordingly.

Abstract
This paper addresses the design, development and experimental tests of a prototype of fuel gas generation system based on biomass gasification for small-scale applications, around 5?kW. It comprises the small scale downdraft gasifier and the gas cleaning system aiming to clean-up the producer gas to be used in the upstream Internal Combustion Engine (ICE). The design of the downdraft gasifier prototype follows the methodologies that have been reported on the available literature. However, since these methodologies apply to gasifiers with larger rated powers, the adopted methodology is based on the extrapolation of the main parameters used for larger gasifiers design. For runing the ICE the producer gas requires to have a specific gas composition with an acceptable range of impurities. Therefore, a clean-up system was proposed following three stages: in first instance a hot gas clean-up using a cyclone designed to eliminate particles and compounds; then a heat exchanger was used for cooling the gas to condensate tars and water; finally a cold gas clean-up is performed by filtration using two filter steps: the first one using organic material (biomass) and the second one using a polypropylene cartridge filter. Experimental tests were performed using the developed imbert downdraft gasifier prototype, using pellets as feedstock. The preliminary results allow verifying several drawbacks that will difficult an effective integration of the developed prototype for small scale power generation applications based on ICE using low density feedstock.

Abstract
In this paper, for the data set of the Iberian Electricity Market for the period 1 January 2015 to 30 June 2019, 19 different models are considered from econometrics, statistics, and artificial intelligence to explain how electricity markets work. This survey allows us to obtain a more complete, critical view of the most cited models. The machine learning models appear to be very good at selecting the best explanatory variables for the price. They provide an interesting insight into how much the price depends on each variable under a nonlinear perspective. Notwithstanding, it might be necessary to make the results understandable. Both the autoregressive models and the linear regression models can provide clear explanations for each explanatory variable, with special attention given to GARCHX and LASSO regression, which provide a cleaner linear result by removing variables that have a minimal linear impact.

Abstract
Energy storage is an important element of an energy system. In the power system, energy storage can be defined as a component that can be employed to generate a form of energy or utilize previously stored energy at different locations or times when it is required. Energy storage can enhance the stability of the grid, increase the reliability and efficiency of integrated systems that include renewable energy resources, and can also reduce emissions. A diverse set of storage technologies are currently utilized for the energy storage systems (ESSs) in a varied set of projects. This chapter provides information about the current ESS projects around the world and emphasizes the leading countries that are developing the applications of ESSs. The main categories of ESSs are explained in this chapter as follows: electrochemical, electromechanical, electromagnetic, and thermal storage. Moreover, the energy storage technologies are utilized in power grids for various reasons such as electricity supply capacity, electric energy time-shifting, on-site power, electric supply reserve capacity, frequency regulation, voltage support, and electricity bill management. Additionally, by integrating the various energy forms and developing the concept of multi-energy systems, ESSs become a fundamental component for the efficient operation of multi-energy systems. The main role of ESSs in multi-energy systems is to compensate for the fluctuations in power output from renewable energy resources. Moreover, the performance of the multi-energy system increases when it got integrated with an ESS. In this chapter, the applied ESS technologies in the context of the multi-energy systems are presented and explained.

Abstract
This work presents a new dump load controller for active power management of hydraulic generator unit using the power system parameters at the generator's terminals. An existing system with an analog controller is evaluated and a new digital open source HPP (Hydraulic power plant) power controller with extended functionality is proposed, designed and realized. A simulation of the voltage measurement sensor in LTspice is performed in order to determine the appropriate hardware parameters. Comparison between the features of the existing analog controller and the new digital controller is performed. Based on the results achieved, valuable conclusions are made. The new solution proposed offers simplified hardware, high reliability, easiness and flexibility of controller settings.

Abstract
Renewable energy communities (REC) are bound to play a crucial role in the energy transition, as their role, activities, and legal forms become clearer, and their dissemination becomes larger. Even though their mass grid integration, is regarded with high expectations, their diffusion, however, has not been an easy task. Its legal form and success, entail responsibilities, prospects, trust, and synergies to be explored between its members, whose collective dynamics should aim for optimal operation. In this regard, the pairing methodology of potential participants ahead of asset dimensioning seems to have been overlooked. This article presents a methodology for pairing consumers, based on their georeferenced load consumptions. A case study in an area of Porto (Asprela) was used to test the methodology. QGIS is used as a geo-representation tool and its PlanHeat plugin for district characterization support. A supervised statistical learning approach is used to identify the feature importance of an overall district energy consumption profile. With the main variables identified, the methodology applies standard K-means and Dynamic Time Warping clustering, from which, users from different clusters should be paired to explore PV as the main generation asset. To validate the assumption that this complementarity of load diagrams could decrease the total surplus of a typical PV generation, 18 pairings were tested. Results show that, even though it is not true that all pairings from different clusters lead to lower surplus, on average, this seems to be the trend. From the sample analyzed a maximum of 36% and an average of 12% less PV surplus generation is observed.