Abstract
This paper discusses some problems related with the current Brazilian electricity market, brings out some dilemmas that should be examined in order to implement a more market oriented approach, and proposes a new market design to overcome these issues. The proposed market design is based on the concept of energy right accounts as virtual reservoirs and aims at enhancing the flexibility to enable market participants to comply with their contracts, while still ensuring the efficient use of the energy resources and maintaining the current security supply level. In addition, in order to simulate the behavior of the market participants in this new framework, an Agent-Based Model - ABM where agents use reinforcement Q-Learning is developed for the study case. The results show that this new market design is suitable to be applied to hydrothermal systems having a large share of hydros.

Abstract
This paper describes an enhanced model for the Short Term Hydro Scheduling Problem, HSP, that includes the impact of operation decisions on the market prices and the possibility of adjusting the tailwater level. Additionally, the efficiency of hydraulic turbines is treated as a variable dependent on the discharged flows. The developed solution algorithm uses an iterative approach that solves in each iteration a linearized HSP problem using the linprog function of the MATLAB (R) Optimization Toolbox. In each iteration, the value of the head to use in the next iteration is updated. The paper reports results from a realistic Case Study based on the cascade of 9 hydro stations (4 of them with pumping) installed in the Portuguese section of the Douro River.

Abstract
Over the last few years, electrical storage and especially battery systems have seen a strong rise in interest. In several countries, as for instance in Germany, lithium-ion batteries are now commonly deployed in end-consumer installations to shift local generation from photovoltaic systems in time. A further application for storage is price arbitrage, which corresponds to an operation strategy benefitting from price differentials. In this work, we describe a Mixed Integer Problem to optimize the storage dispatch considering both the 15- and the 60-min auctions in use in Germany. Furthermore, in addition to the calendric lifetime, the limitation to a certain number of cycles is considered in the evaluation. Last, it was conducted a sensitivity analysis to identify the price volatility level that is required to generate a profit from arbitrage operations. Therefore, a market price process with adjustable parameters has been implemented.

Abstract
Electric vehicles will certainly play an important and increasing role in the transport sector over the next years. As their number grows, they will affect the behavior of the electricity demand seen not only by distribution but also by transmission networks and so changes will also occur in the operation and expansion planning of the power systems. In this sense, this paper addresses the impact of large fleets of Plug-in-Electric Vehicles (PEVs) in transmission equipment investments. The developed model uses evolutionary particle swarm optimization (EPSO) to handle the planning problem over different scenarios regarding the evolution of PEVs and their impact on the demand. These scenarios consider the PEVs penetration level, the availability of charging and the related charging policies. The paper includes a Case Study based on the IEEE 24 busbar power system model for a 10-year period. The model uses an AC Optimal Power Flow to analyse the operation of the system for different investment paths over the years and the results show that coordinating the charging of PEVs can be an interesting solution to postpone the investments in transmission equipment thus reducing the associated costs.

Abstract
The Brazilian electricity market is characterized by having around 65% of its installed capacity coming from hydropower plants, with multiple agents coexisting in the same hydro cascades. Currently, it also contains certain peculiarities that distinguish it from other markets, such as the Energy Reallocation Mechanism (MRE), a centerpiece of the Brazilian market's design. This paper proposes replacing the MRE with a bid-based short-term market called the virtual reservoir model. To simulate the behavior of the hydros in this new market, an agent-based model is implemented using the reinforcement Q-learning algorithm, simulated annealing and linear programming. In the simulations, we use real data - encompassing more than 98% of the total hydro installed capacity and three years of market data - from the Brazilian power system. The results indicate that the management of (virtual) reservoirs can be the responsibility of each hydro: these can save water according to their own risk perceptions, while maintaining current efficiency and security levels. The results also suggest that the final monthly short-term market prices can substantially decrease in comparison with the current prices.

Abstract
A flexible control of the distribution system is an efficient strategy to enhance the grid reliability and quality of service, in this sense, the maneuver devices play an important role to reach flexibility under network faults. In this direction, the present work proposes a new approach to solve the allocation problem of optimal maneuver devices in electric distribution systems (EDS) that considers both permanent and temporary faults. The considered maneuver devices are normally closed switches coupled to the beginning or to the end of distribution branches. The objective is to improve the system reliability with minimal investment cost. The metaheuristic and bio-inspired technique known as artificial immune system (AIS) is applied to handle the discrete feature of the switch allocation problem. The index considered to evaluate the reliability is the system expected outage cost to customers due to supply outages (ECOST). The paper includes a case study with four different simulations using the well-know RBTS Bus 4 test system The obtained results were compared to the literature ones and proved that the proposed approach can lead to promising solutions that establish a suitable trade-off between the reliability and the utility costs. © 2018 Power Systems Computation Conference.