Abstract
Vast increase of renewable energy resources' (RER) share in total electricity production have led to evolving studies regarding different aspects of renewables integration. Other than their effects on network, the electricity markets are also affected by uncertain behavior of RERs in the market place. Hence, new approaches for market clearing are investigated. One of the possible solutions is the deployment of stochastic market clearing. However, the adaption of new market models should consider different market characteristics. As a result, this paper assesses the adaption of stochastic market in a hydro-penetrated system. The co-optimized energy and reserve schedule in the day-ahead time frame is derived using the mixed integer linear programming (MILP). The model is tested with Portuguese electricity market data as a real-case of hydro-penetrated system.

Abstract
In this paper, a mixed-integer linear programing (MILP) model for characterizing the traffic behavior of plug-in electric vehicles (PEVs) in an urban environment is proposed. The paper proposes the procedure to mathematically model the uncertain behavior of the PEVS. As the PEV's traffic pattern affects the potential of PEV parking lot (PL) in terms of available capacity and state of charge, the characterized PEVs are employed to provide the proper pricing schemes for the PEVs in PL. The results discuss the mutual effect of PEVs behavior on the profit of PL, as well as the effects of PL's tariffs on motivating PEVs to provide more flexibility for the PL. The results show that with a proper pricing scheme both parties (i.e., PEV owners and PL) can earn higher profits, while the charging requirements are met based on the preferences of the owners.

Abstract
The introduction of plug-in electric vehicles (PEVs) in the electrical system is bringing various challenges. One of the recent solutions to deploy the potentials of PEVs in the system is through PEV parking lots (PL). The PLs not only provide a place for the PEVs charging requirements, but also give the possibility of exploiting the vehicle-to-gird (V2G) potential of PEVs in a more efficient manner comparing to PEV aggregators. On the other hand, the V2G mode gives the reserve market possibility to the PL operator, which can be a source of income other than selling energy to the PEV owners. However, the willingness of participating in the V2G mode may be low due to exposing battery degradation and not sufficient departure state of charge (SOC). As a result, this study investigates the behavior of PL on deploying the V2G mode of PEVs in reserve market participation considering the PEVs' traffic behavior.

Abstract
Emerging technologies arising in modern power systems have propelled the presence of new agents to manipulate these facilities. Participation of plug-in electric vehicles (PIEVs) in the electricity market is one of the main issues in this environment. PIEV participation in market place can affect the agent's strategy. Therefore, this paper investigates two states of power system where individual aggregators participate in the power market on behalf of home-charged PIEVs and parking lots (PLs) separately, as well as the coordinated version of the problem. Several scenarios are developed for deriving specific characteristics of PIEVs in home levels and in PLs. An optimization model is built and solved using mixed integer linear programming. The results are produced to suggest the optimum procedure for an aggregator to whether take the authority of home-charging PIEVs and PLs individually or coordinately.

Abstract
In this paper, an innovative bi-level model is developed for the interactions of the plug-in electric vehicle (PEV) parking lot (PL) with the upstream markets through an aggregator in the system. The preferences of the PEVs on using the PL are also considered in the study. The PEVs have a choice in participating in grid-to-vehicle or vehicle-to-grid modes with fixed or flexible amount of departed state of charge (SOC). The PL assigns various tariffs for different requirements of the PEVs. In this study, the mutual effect of the variation of PEV tariffs and the PL's behavior in the market is investigated. It is shown that the preferences of PEVs can significantly affect the PL's strategy. The changes of the equilibrium prices for PL and aggregator interaction are thoroughly analyzed in response to changes in PEV tariffs to illustrate their influence on their behavior.

Abstract
The inevitable need of new infrastructures for encouraging plug-in electric vehicles (PEVs) penetration into the system has drawn various attentions towards the required studies. In this regard, the PEVs parking lot (PL) has shown to have proper potentials. Other than providing a charging place for the PEVs, PLs can be considered as an integrated form of PEV batteries and act as storage in the system. However, the accuracy of PL's operation can be enhanced through detailed modeling of various affecting factors such as PEV's preferences on using the charging capability of the PL. In this study, a new model to add the PEVs' preferences in the PL's market participation problem is proposed. Various categories of PEVs are considering based on their arrival/departure pattern, duration of stay in the PL, and charging requirements. The results showed a considerable difference in PL's strategy in market participation, with and without considering PEVs' preferences.