Abstract
Power-to-Hydrogen (P2H) clean systems have been increasingly adopted for Virtual Power Plant (VPP) to drive system decarbonization. However, current models for the joint operation of VPP and P2H often disregard the full impact on grid operation or hydrogen supply to multiple consumers. This paper contributes with a VPP operating model considering a full Alternating Current Optimal Power Flow (AC OPF) while integrating different paths for the use of green hydrogen, such as supplying hydrogen to a Combined Heat and Power (CHP), industry and local hydrogen consumers. The proposed framework is tested using a 37-bus distribution grid and the results illustrate the benefits that a P2H plant can bring to the VPP in economic, grid operation and environmental terms. An important conclusion is that depending on the prices of the different hydrogen services, the P2H plant can increase the levels of self-sufficiency and security of supply of the VPP, decrease the operating costs, and integrate more renewables.

Abstract
Although electric vehicle (EV) sales have been increasing over the years, worldwide EV adoption is still low. In Brazil, the key factors influencing this are the EV high acquisition cost and the reduced charging infrastructure. Therefore, traditional business models may not be adequate for Brazil and stagnate EV diffusion. Thus, designing innovative business models can be crucial to accelerate the transition to electric mobility in the region. In this way, this article aims to critically review business models for EV adoption and charging stations worldwide and discuss its application in Brazil. Then, the challenges and opportunities for some business model options are highlighted through the SWOT matrix. One can conclude that EV sharing is a promising business model for Brazil, given the series of advantages such as access to cutting-edge technology at an affordable price, reduction of vehicles on the streets, and given convenience for users (no concern with charging, EV degradation, and parking). However, public policies, subsidies, and coordination between different agents are crucial for the proliferation of this model. On the other hand, for the proposed CS models, the more traditional option is the less risky for investors in Brazil until the number of EVs increase.

Abstract
Integration of prosumers in district heating networks brings new challenges to the market and the network operation since they can change the thermal flow and increase competition. Thus, it is mandatory to develop new market structures and network management mechanisms. In this scope, this work proposes the implementation of a coordination methodology based on a peer-to-peer market without a supervising entity. The goal is to achieve higher revenue by coping with the requirements of each agent. Furthermore, the model is validated through network nodal analysis inspired by the power sector. The results in a Nordic network point out that the coordination methodology can provide compromise solutions between market negotiation and network operation. This methodology succeeded in providing reliable network solutions, fixing 99.88% of network burdens just after one iteration, and encouraging prosumers' integration. This increases market competition which lowers the energy costs for consumers while avoiding the network's operating burdens.

Abstract
The increasing integration of Distribution Energy Resources (DER) in the distribution system has brought the necessity of a change in grid management and also for better coordination between the Transmission System Operator (TSO) and the Distribution System Operator (DSO). This work proposes a reactive power management model to be used by DSOs, in which reactive power flexibility from DER, and also from On-Load Tap Changer (OLTC) transformers and capacitor banks are used to handle voltage problems that may arise in both transmission and distribution grids due to the uncertain production of Renewable Energy Sources (RES). Besides, it is proposed that the DSO may provide a service to the TSO, in which the latter requests a reactive power setpoint from the first one, in the TSO-DSO boundary. Adaptive robust optimization on an Alternating Current Optimal Power Flow (AC-OPF) is modelled, ensuring that the DSO receives a feasible solution and is able to manage congestion and voltage problems. The proposed model is compared with its stochastic equivalent to assess its strengths and drawbacks. To test and validate the proposed models, a 37-bus Medium Voltage (MV) distribution grid with high RES penetration is used. An important conclusion is that, though the robust model presents a safer solution than the stochastic model, the operator must be aware of the trade-off between the desired level of robustness and the expected operating cost.

Abstract
The rising potential for battery energy storage systems (BESS) to generate revenue in a market environment is addressed in this work, where a tool based on neural network predictions is proposed. The tool's main objective is predicting, based on historical data, the most lucrative out of three established bidding approaches for the participation of a BESS in the day-ahead energy market and thus aid the strategic bidding process of the BESS operator. Each of these bidding strategies reflects BESS's operator approach concerning bidding frequency and the tolerated risk of loss of profit from having its bids rejected, leading to the development of a conservative (strategy A), an aggressive (strategy B), and a moderate strategy (strategy C). A case study was then used to test the tool for a full year allowing to ascertain the assertiveness of this tool in predicting the best strategy, which for this case was above 88%.

Abstract
This work models a distributed community-based market with diverse assets (photovoltaic generators and energy storage systems), accounting for network constraints and adopting the relaxed branch flow model. The market is modeled in a single and fully distributed approach, employing the alternating direction method of multipliers (ADMM) to prevent voltage and line capacity problems in the community network and improve data privacy and reduce the communication burden. Different scenarios, based on the penalty term and the agents' number, are tested to study the efficiency of the algorithm and the convergence rate of the ADMM distributed model. The proposed method is tested on 10-bus, 22-bus, and 33-bus medium voltage radial distribution networks, where each node contains a large prosumer with one or several assets. One important conclusion is that the implemented residual balancing technique improves the efficiency of the ADMM distributed algorithm by increasing the convergence rate and reducing the computational time.