Abstract
In recent years, in addition to the traditional aspects concerning efficiency and profitability, the energy sector is facing new challenges given by environmental issues, security of supply, and the increasing role of the local demand. Therefore, the researchers have developed new decision-making frameworks enabling higher local integration of distributed energy resources (DER). In this context, new energy players appeared in the retail markets, increasing the level of competition on the demand side. In this paper, a multienergy player (MEP) is defined, which behaves as a DER aggregator between the wholesale energy market and a number of local energy systems (LES). The MEP and the LES have to find a long-term equilibrium in the multienergy retail market, in which they are interrelated through the price signals. To achieve this goal, in this paper the decision-making conflict between the market players is represented through a bilevel model, in which the decision variables of the MEP at the upper level are parameters for the decision-making problem at the lower level (for the individual LES). The problem is transformed into a mathematical program with equilibrium constraints by implementing duality theory, which is solved with the CPLEX 12 solver. The numerical results show the different MEP behavior in various conditions that impact on the total flexibility of the energy system.

Abstract
This paper addresses the location of parking lots (PLs) to be used for plug-in electric vehicles (PEVs) by using a probabilistic traffic model and taking into account the PL participation in electricity markets. The PLs are used both for grid-to-vehicle and vehicle-to-grid. The system includes private or public charging stations only used for PEV charging. The traffic model considers the partitioning of the territory into areas. The case study is based on traffic and market data referring to Italy.

Abstract
In this paper, a mixed-integer linear programing (MILP) model for the stochastic clearing of electricity markets with probabilistic participants is proposed. It is assumed that the sources of uncertainty in the market comes both from generation and demand side. The wind generating unit and electric vehicle aggregator are the supposed sources of uncertainty in the system. For the compensation of probable deviation of stochastic participants, flexible generation and demand will offer for the reserve activation. The two-stage model takes into account the day-ahead cost as well as the expected balancing costs due to probabilistic behavior of uncertain participants. A scenario-based approach is used to model the probabilistic participants. The proposed model stochastically clears the market and the results discuss the lower costs obtained by incorporating various resources of uncertainty and flexibility in the market.

Abstract

Abstract
Strong adoption dynamics of private passenger electric vehicles (EV) will require adjustments in the operation and planning of electrical distribution grids. This work proposes a novel approach to assess the impact of electric vehicle charging while considering EV adoption dynamics and commuting patterns. The proposed model uses Geographic Information Systems (GIS) and is applied to a real-world case study. Results suggest that clustering of EV charging will occur and underline the relevance of accurate spatial and temporal charging pattern estimations for distribution grid planning. Overloading of distribution network elements was observed even under light EV penetration rates.

Abstract
The multi-energy systems (MES) contain key resources driving the evolution of the future systems. Various components and convertors that are available in a MES make it operationally flexible and a potential source to be deployed in system operation. Like any other resources in the system, the flexibility brought by MES needs to be fairly valued. One of the approaches is through market participation of these resources. In this regard, new agents and trade system need to be defined. This paper studies the interactions of a multi-energy aggregator on various trade levels defined within the multi-energy paradigm. The levels include the upstream multi-energy markets as well as local energy trades such as local resources and flexible demand. The results discuss the increased level of profit due to the availability of multi-energy trade to the aggregator.