Abstract
The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

Abstract
In recent years the reassessment of remuneration schemes for renewable sources in several European countries has motivated the increase of wind power generation participation in electricity markets. Moreover, the continuous growth of wind power generation, as well as the evolution of wind turbines technology, suggests that wind power plants may participate in both energy and ancillary services markets with strategic behavior to improve their benefits. Thus, wind power generation with strategic behavior may have impact on market equilibrium and pricing. This paper evaluates the impact of a proportional offering strategy for wind power plants to participate in both energy and ancillary services markets. MASCEM (Multi-Agent System for Competitive Electricity Markets) is used to simulate and validate the impact of wind power plants in market equilibrium. A case study based on real and recent data for the Iberian market and its specific rules is simulated in MASCEM. © 2015 IEEE.

Abstract
In recent years the reassessment of remuneration schemes for renewable sources in several European countries has motivated the increase of wind power generation participation in electricity markets. Moreover, the continuous growth of wind power generation, as well as the evolution of wind turbines technology, suggests that wind power plants may participate in both energy and ancillary services markets with strategic behavior to improve their benefits. Thus, wind power generation with strategic behavior may have impact on market equilibrium and pricing. This paper evaluates the impact of a proportional offering strategy for wind power plants to participate in both energy and ancillary services markets. MASCEM (Multi-Agent System for Competitive Electricity Markets) is used to simulate and validate the impact of wind power plants in market equilibrium. A case study based on real and recent data for the Iberian market and its specific rules is simulated in MASCEM.

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.

Abstract
In this paper, a mixed-integer linear programing ( MILP) model for the traffic behavior of plug-in electric vehicles ( PEVs) in an urban environment is proposed. It is assumed that any environment can be categorized into different zones based on their urban functions ( e. g. industrial, residential, and commercial). Therefore, the interaction of PEVs that travel between these zones has to be modeled. Besides, it is assumed that in each zone a parking lot ( PL) and individual charging stations exist to provide the required state of charge ( SOC) for PEVs during their daily travel. As a result, the amount of power that these PEVs consume ( rather in PL or charging stations) and the amount of SOC that PEVs carry with them should be precisely computed. The proposed MILP model is applied on two zones urban area with residential and industrial districts and the numerical results prove the proficiency of the model.