Abstract
The charging behavior of electric vehicles (EVs) is a key concern to system operators and retailers given a massive adoption these resources. System operators and retailers may profit from the handling of EVs as flexible loads. The former has interest to move their charging into periods without congestion and voltage problems. Similarly, the latter wants them to only charge at periods when energy is cheaper. This paper addresses the problem by modelling a real-time tariff to encourage flexible EVs charging behavior. More precisely, different tariffs are modelled based on the relation between wind power generation, load consumption and spot price, while assuming Denmark as showcase. The EVs behavior entails three different patterns and a socioeconomic term that defines the anxiety of EVs users' to be responsive to the tariffs. An important conclusion is that a proper real-time tariff design can reduce the energy costs for the retailer and EVs.

Abstract
Increasing power injection of distributed energy resources (DER) (including prosumers) has been changing the way the distribution system is operated and managed. Thus, conventional network usage tariffs are no longer fair enough to distribute the network costs to the various system participants. Within this scope, this work studies innovative cost allocation models that fairly distribute fixed, network usage and power losses costs to all system participants. A three-stage model is designed, in which: (i) an alternating current optimal power flow (AC OPF) for the distribution grid is performed; (ii) two different power tracing models (namely, the Abdelkader's and Bialek's tracing methods) are implemented and compared; and (iii) the distribution of costs through a MW-mile variant. The model is tested and validated in a 33-node distribution network considering high penetration of DER. © 2019 IEEE.

Abstract
The current coordination between the transmission system operator (TSO) and the distribution system operator (DSO) is changing mainly due to the continuous integration of distributed energy resources (DER) in the distribution system. The DER technologies are able to provide reactive power services helping the DSOs and TSOs in the network operation. This paper follows this trend by proposing a methodology for the reactive power management by the DSO under renewable energy sources (RES) forecast uncertainty, allowing the DSO to coordinate and supply reactive power services to the TSO. The proposed methodology entails the use of a stochastic AC-OPF, ensuring reliable solutions for the DSO. RES forecast uncertainty is modeled by a set of probabilistic spatiotemporal trajectories. A 37-bus distribution grid considering realistic generation and consumption data is used to validate the proposed methodology. An important conclusion is that the methodology allows the DSO to leverage the DER full capabilities to provide a new service to the TSO.

Abstract
The adoption of Electric Vehicles (EVs) will revolutionize the storage capacity in the power system and, therefore, will contribute to mitigate the uncertainty of renewable generation. In addition, EVs have fast response capabilities and are suitable for frequency regulation, which is essential for the proliferation of intermittent renewable sources. To this end, EV aggregators will arise as a market representative party on behalf of EVs. Thus, this player will be responsible for supplying the power needed to charge EVs, as well as offering their flexibility to support the system. The main goal of EV aggregators is to manage the potential participation of EVs in the reserve market, accounting for their charging and travel needs. This work follows this trend by conceiving a chance-constrained model able to optimize EVs participation in the reserve market, taking into account the uncertain behavior of EVs and their charging needs. The proposed model, includes penalties in the event of a failure in the provision of upward or downward reserve. Therefore, stochastic and chance-constrained programming are used to handle the uncertainty of a small fleet of EVs and the risk profile of the EV aggregator. Two different relaxation approaches, i.e., Big-M and McCormick, of the chance-constrained model are tested and validated for different number of scenarios and risk levels, based on an actual test case in Denmark with actual driving patterns. As a final remark, the McCormick relaxation presents better performance when the uncertainty budget increases, which is appropriated for large-scale problems.

Abstract
The increasing penetration of distributed energy resources, along with developments in house management systems, are supporting prosumers to play an active role in the electricity market. In particular, a peer-to-peer (P2P) electricity market is an attractive framework to allow direct transactions between prosumers. However, this may raise several challenges in the operation and management of the distribution grid. In this context, the main contribution of this paper is the design of P2P electricity markets taking into account grid characteristics while solving potential congestion and voltage problems. The paper proposes a coordination methodology between P2P markets and distribution system operator (DSO) allocating a grid tariff to the prosumers that cause grid limit violations. Such tariff is defined based on the euclidean distance among trading prosumers, which is implemented in the P2P market through product differentiation approach. The proposed methodology is compared to a benchmark model in a representative distribution grid with 138 nodes and 109 prosumers. An important conclusion is that the proposed methodology is capable of achieving a trade-off between prosumers P2P transactions and grid operation.

Abstract
This paper presents a comprehensive study of the technical and economic benefits that a typical residential prosumer may experience when investing in a solar photovoltaic (PV) system with a battery energy storage system (BESS). To this end, a home energy management system has been designed to simulate the prosumer's daily operation, considering a novel method for calculating battery degradation while minimizing its operating costs. In order to contribute to the regulatory review process of the distributed generation underway in Brazil, a set of PV+BESS configurations has been assessed under the current and future regulatory scenarios proposed for discussion by the Brazilian regulatory agency. Although the results demonstrate that the prosumer's self-consumption rate may increase up to 14% with the BESS coupling in the PV system, the investment proved to be economically unattractive in the current regulatory scenario and practically unfeasible in any of the proposed future scenarios. To make PV+BESS systems economically feasible, some business models are proposed and discussed, and for example, provide subsidies for policymakers, financial agents, and battery manufacturers. A sensitivity analysis for each business model showing its economic feasibility spectrum is provided to assist the different sector players, especially the consumers, in their decision-making process.