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.

The development of Urban-Scale Energy Modelling (USEM) at the district or city level is currently the goal of many research groups due to the increased interest in evaluating the impact of energy efficiency measures in city environments. Because USEM comprises a great variety of analysis areas, the simulation programs that are able to model urban-scale energy systems actually consist of an assemblage of different particular sub-models. In order to simulate each of the sub-models in USEM, one can choose to use either existing specific simulation engines or tailor-made models. Engines or tools for simulation of urban-scale energy systems have already been overviewed in previous existing literature, however the distinction and classification of tools according to their functionalities within each analysis area in USEM has not been clearly presented. Therefore, the present work aims at reviewing the existing tools while classifying them according to their capabilities. The ultimate goal of this classification is to expose the available resources for implementing new co-simulation approaches in USEM, which may reduce the modelling effort and increase reliability as a result of using established and validated simulation engines.

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European energy policies call for an increased share of renewable energy sources and a more active role of the energy consumer. This is facilitated by, amongst others, buildings becoming energy flexible hubs, supporting smart energy grids with demand response strategies. While there is abundant technical research in this field, the related business and policy development is less well documented. This research scopes existing policy programmes and identifies opportunities and barriers to business development supporting energy flexible buildings. Using examples from seven European countries, this work reviews influencing niche management factors such as existing policy instruments, business development cases and identified stakeholder concerns, using literature research, narrative analysis and stakeholder research.National policy pathways show many differences but confirm that European buildings might become active players in the energy market, by providing energy storage, demand response and/or shifts in the use of energy sources. Slow sustained business development for energy flexibility services was mainly identified in the retail industry, and for energy service companies and aggregators. The direct involvement of end users in energy flexible buildings is still difficult. Stakeholders call for policy improvement, especially concerning the development of flexible energy tariffs, supporting incentives, awareness raising and more stakeholder-targeted business development.

The recent cost reduction and technological advances in medium-to large-scale Battery Energy Storage Systems (BESS) makes these devices a true alternative for wind producers operating in electricity markets. Associating a wind power farm with a BESS (the so-called Virtual Power Plant (VPP)) provides utilities with a tool that converts uncertain wind power production into a dispatchable technology that can operate not only in spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, were forbidden to non-dispatchable technologies. What is more, recent studies have shown capital cost investment in BESS can be recovered only by means of such a VPP participating in the ancillary services markets. We present in this study a multistage stochastic programming model to find the optimal operation of a VPP in the day-ahead, intraday and secondary reserve markets while taking into account uncertainty in wind power generation and clearing prices (day-ahead, secondary reserve, intraday markets and system imbalances). A case study with real data from the Iberian Electricity Market is presented.

A major issue in modelling the electrical load of residential building is reproducing the variability between dwellings due to the stochastic use of different electrical equipment. In that sense and with the objective to reproduce this variability, a stochastic model to obtain load profiles of household electricity is developed. The model is based on a probabilistic approach and is developed using data from the Mediterranean region of Spain. A detailed validation of the model has been done, analysing and comparing the results with Spanish and European data. The results of the validation show that the model is able to reproduce the most important features of the residential electrical consumption, especially the particularities of the Mediterranean countries. The final part of the paper is focused on the potential applications of the models, and some examples are proposed. The model is useful to simulate a cluster of buildings or individual households. The model allows obtaining synthetic profiles representing the most important characteristics of the mean dwelling, by means of a stochastic approach. The inputs of the proposed model are adapted to energy labelling information of the electric devices. An example case is presented considering a dwelling with high performance equipment.