Abstract-An optimization model is proposed to manage a residential microgrid including a charging spot with a vehicle-togrid system and renewable energy sources. In order to achieve a realistic and convenient management, we take into account: (1) the household load split into three different profiles depending on the characteristics of the elements considered; (2) a realistic approach to owner behavior by introducing the novel concept of range anxiety; (3) the vehicle battery management considering the mobility profile of the owner and (4) different domestic renewable energy sources. We consider the microgrid operated in grid-connected mode. The model is executed one-day-ahead and generates a schedule for all components of the microgrid. The results obtained show daily costs in the range of 2.82eto 3.33e; the proximity of these values to the actual energy costs for Spanish households validate the modeling. The experimental results of applying the designed managing strategies show daily costs savings of nearly 10%.Index Terms-Optimal management, smart grids, vehicle-togrid (V2G), range anxiety, renewable generation, residential microgrids I. NOTATION Sets RSet of devices with shiftable load, r ∈ R T Set of time intervals, t ∈ T U wIntervals where the EV is plugged D UE to the current development of electric vehicle (EV) technology and its commercialization, the integration of the EV in the optimal management of residential energy systems will become a real need in the medium term. Moreover, the EV penetration levels could be increased if EV users' concern about running out of electricity before reaching their destination is mitigated. This increase would favour the environment aligning with the European energy objectives.

This paper proposes a methodology for the economic optimisation of the sizing of Energy Storage Systems (ESSs) whilst enhancing the participation of Wind Power Plants (WPP) in network primary frequency control support. A generalised approach was taken for the design of the methodology, so it can be applied to different energy markets and concerning different ESSs. The methodology includes the formulation and solving of a Linear Programming (LP) problem.The methodology was applied to the particular case of a 50 MW WPP, equipped with Vanadium Redox Flow battery (VRB) in the UK energy market. Analysis is performed considering real data on the regular and frequency response markets of UK. Data for wind power generation and energy storage costs are estimated from literature.Results suggest that, under certain assumptions, ESSs can be profitable for the operator of a WPP that is providing frequency response. The ESS provides power reserves such that the WPP can generate close to the maximum energy available. The solution of the optimisation problem establishes that an ESS with a power rating of 5.3 MW and energy capacity of about 3 MWh would be enough to provide such service whilst maximizing the incomes for the WPP operator considering the regular and frequency regulation UK markets.Methodology for the economic optimisation of energy storage systems for frequency support in wind power plants Abstract This paper proposes a methodology for the economic optimisation of the sizing of Energy Storage Systems (ESSs) whilst enhancing the participation of Wind Power Plants (WPP) in network primary frequency control support. A generalised approach was taken for the design of the methodology, so it can be applied to different energy markets and concerning different ESSs. The methodology includes the formulation and solving of a Linear Programming (LP) problem.The methodology was applied to the particular case of a 50 MW WPP, equipped with Vanadium Redox Flow battery (VRB) in the UK energy market. Analysis is performed considering real data on the regular and frequency response markets of UK. Data for wind power generation and energy storage costs are estimated from literature.Results suggest that, under certain assumptions, ESSs can be profitable for the operator of a WPP that is providing frequency response. The ESS provides power reserves such that the WPP can generate close to the maximum energy available. The solution of the optimisation problem establishes that an ESS with a power rating of 5.3 MW and energy capacity of about 3 MWh would be enough to provide such service whilst maximizing the incomes for the WPP operator considering the regular and frequency regulation UK markets.

Abstract-The aim of this paper is to find the optimal location of electric vehicle (EV) fast charging stations by means of two methodologies: a classical flow-capturing optimization model involving only mobility needs, and an advanced flow-capturing optimization model including distribution network and location costs. While the first model aims to maximize the public service provided by the fast charging stations, the second also considers the incurred cost for providing it. Results from both models are compared in order to analyse the effect of both planning approaches in total cost of installation. As a case study it has been chosen the city of Barcelona.

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