Abstract
In this paper, the management of PEVs, uncontrolled or controlled (i.e. aggregated), and their ability to use V2G and G2V technologies are first analysed. The electricity markets are then considered; real world applications are discussed and different market types categorised. The interaction of the PEVs with some renewable energy sources (e.g. solar, wind and biomass) is also examined, and the interaction of the PEVs with demand response programs addressed. Finally, the models of PEVs are categorised and multiple types of modules, the related variables, applied methods and the considered parameters are presented.

Abstract
In this paper, a multi energy system (MES) model incorporating the traffic behavior of plug-in electric vehicles (PEVs) is proposed. It is assumed that in a micro MES two charging options are available for the PEVs: the home charging (HC) stations and the PEV parking lot (PL). The operation of these elements within the micro MES concept is studied. The matrix model of the micro MES is adapted to enable the integration of PL and HC. Moreover, the traffic flow of the PEVs is added to the model as an input to the micro MES. The model is tested for various case studies and possible traffic behavior between the PL and HC. The results show that the presence of these two elements leads to effective integration of reduced system operation costs.

Abstract
This paper proposes a comprehensive model for the interactions of the plug-in electric vehicles (PEVs) involved parties. An aggregator with mixed resources is assumed to be the interface between the parking lot (PL) and the upstream energy and reserve markets. On the other hand, the interactions of the PEV owners and the PL are also modeled as they impose restrictions to the PL's behavior. Therefore, a bilevel problem is constructed where in the upper level the objective of the aggregator is to maximize its profit through its interactions, and in the lower level the PL maximizes its own profit limited to the preferences of PEVs. The objectives of the upper and lower levels are contradictory; hence, an equilibrium point should be found to solve the problem. In this regard, the duality theorem is employed to convert the bilevel model to a mathematical program with equilibrium constraints. The model is implemented on the IEEE 37-bus network with added distributed generations. Various cases are thoroughly investigated and conclusions are duly drawn.

Abstract
In recent years, the level of variable Renewable Energy Sources (vRESs) integrated in power systems has been increasing steadily. This is driven by a multitude of global and local concerns related to energy security and dependence, climate change, etc. The integration of such energy sources is expected to continue growing in the coming years. Despite their multifaceted benefits, variable energy sources introduce technical challenges mainly because of their intermittent nature, particularly at distribution levels. The flexibility of existing distribution systems should be significantly enhanced to partially reduce the side effects of vRESs. One way to do this is using a dynamic network reconfiguration. Framed in this context, this work presents an optimization problem to investigate the impacts of grid reconfiguration on the level of integration and utilization of vRES power in the system. The developed combinatorial model is solved using a genetic algorithm. A standard IEEE 33-node distribution system is employed in the analysis. Simulation results show the capability of network switching in supporting large-scale integration of vRESs in the system while alleviating their side effects. Moreover, the simultaneous consideration of vRES integration and network reconfiguration lead to a better voltage profile, reduced costs and losses in the system.

Abstract
Modernization of electricity networks is currently being carried out using the concept of the smart grid; hence, the active participation of end-user consumers and distributed generators will be allowed in order to increase system efficiency and renewable power accommodation. In this context, this paper proposes a comprehensive methodology to optimally control lead-acid batteries operating under dynamic pricing schemes in both independent and aggregated ways, taking into account the effects of the charge controller operation, the variable efficiency of the power converter, and the maximum capacity of the electricity network. A genetic algorithm is used to solve the optimization problem in which the daily net cost is minimized. The effectiveness and computational efficiency of the proposed methodology is illustrated using real data from the Spanish electricity market during 2014 and 2015 in order to evaluate the effects of forecasting error of energy prices, observing an important reduction in the estimated benefit as a result of both factors: 1) forecasting error and 2) power system limitations.

Abstract
This paper investigates the effectiveness of using different decision-making frameworks in local energy systems (LES) through the assessment of the long-term equilibrium of energy players. For this purpose, the energy system is modelled through two levels of multi-energy player (MEP) and LES, coupled by energy price signals. The conflict between the decision-making of these two levels of players is modelled through a bi-level approach. A mathematical problem with equilibrium constraint is formulated by applying the duality theory, resorting to a linear representation of the constraints. The solution is found by using the CPLEX12 solver. The numerical results show the characteristics of the MEP behaviour in different energy aggregation modes for the LES, with centralised management or uniform pricing. The MEP may find benefits from possible synergies among the LES due to availability of energy carriers with complementary characteristics.