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Flexible distributed energy resources, such as energy storage systems (ESSs), are increasingly considered as means for mitigating challenges introduced by the integration of stochastic, variable distributed generation (DG). The optimal operation of a distribution system with ESS can be formulated as a multi-period optimal power flow (MPOPF) problem which involves scheduling of the charging/discharging of the ESS over an extended planning horizon, e.g., for day-ahead operational planning. Although such problems have been the subject of many works in recent years, these works very rarely consider uncertainties in DG, and almost never explicitly consider uncertainties beyond the current operational planning horizon. This article presents a framework of methods and models for accounting for uncertainties due to distributed wind and solar photovoltaic power generation beyond the planning horizon in an AC MPOPF model for distribution systems with ESS. The expected future value of energy stored at the end of the planning horizon is determined as a function of the stochastic DG resource variables and is explicitly included in the objective function. Results for a case study based on a real distribution system in Norway demonstrate the effectiveness of an operational strategy for ESS scheduling accounting for DG uncertainties. The case study compares the application of the framework to wind and solar power generation. Thus, this work also gives insight into how different approaches are appropriate for modeling DG uncertainty for these two forms of variable DG, due to their inherent differences in terms of variability and stochasticity.

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A potentially beneficial new opportunity is emerging around the exchange of energy between electric vehicles and the electrical energy grid, particularly as more low-carbon energy sources are connecting to the grid. Accordingly, this paper presents an optimization framework to activate the potential capabilities of electric vehicles equipped with bidirectional chargers for energy conditioning (including energy management and power quality improvement) of the future distribution networks. The proposed nonlinear optimization seeks to concurrently enhance the operation performance (using the network voltage deviation index) as well as power quality of the grid (using total harmonic distortion index). The proposed model is tested on a 33-bus distribution network to demonstrate its efficiency and performance.

Highlights 13 The cost-optimal choice of energy technologies in a ZEB is determined 14  This paper presents a methodology for determining ZEB buildings' cost optimal energy system design 24 seen from the building owner's perspective. The added value of this work is the inclusion of peak load 25 tariffs and feed-in-tariffs, the facilitation of load shifting by use of a thermal storage, along with the 26 integrated optimisation of the investment and operation of the energy technologies. The model allows for 27 detailed understanding of the hourly operation of the building, and how the ZEB interacts with the 28 electricity grid through the characteristics of its net electric load profile. The modelling framework can be 29 adapted to fit individual countries' ZEB definitions. The findings are important for policy makers as they 30 identify how subsidies and EPBD's regulations influence the preferred energy technology choice, which 31 subsequently determines its grid interaction. A case study of a Norwegian school building shows that the 32 heat technology is altered from HP to bio boiler when the ZEB requirement is applied. 33

This paper presents the design of a single-phase electric vehicle (EV) on-board bidirectional charger with the capability of power conditioning. This charger can control its charging/discharging active power based on the demand of EV battery/network or load. Also, it controls reactive power and harmonic current based on the characteristics of the non-linear and linear loads. The topology of the proposed charger consists of the bidirectional AC/DC and buck-boost DC/DC converters, where it can operates in four quadrants in the active-reactive power plane with the capability of harmonic compensation. In the next step, this paper presents a suitable control strategy for the bidirectional charger according to the instantaneous active and reactive power (PQ) theory. Based on the PQ theory, the active and reactive power that include average and oscillatory components obtained based on the demand of non-linear/linear loads and EV battery. Then, the reference current of AC/DC converter of the charger and battery is obtained, and in the next step, the situation of the charger switches is determined using output signals of the proportional-integral and proportional-resonant controllers and pulse width modulation. Finally, the proposed approach is validated and implemented in the OPAL-RT to integrate the fidelity of the physical simulation and the flexibility of the numerical simulations.

Abstract-This study proposes combined framework for proactive operation, i.e. bidirectional active and reactive power 14 management, of the smart distribution network as well as harmonic compensation of non-linear loads using electric vehicles 15 (EVs) equipped with bidirectional chargers. The problem is in the form of non-linear programming (NLP) where the objective 16 function is to minimise the voltage deviation at the fundamental frequency and the total harmonic distortion. The harmonic load 17 flow equations, EVs constraints, system operation and harmonic indexes limits are formulated as problem constraints. The 18 proposed NLP problem is converted to an equivalent mixed integer linear programming (MILP) model using Taylor series and 19 linearisation techniques for AC power flow formulation. Also, the Benders decomposition (BD) algorithm is used to solve the 20proposed MILP problem that is tested on different distribution test networks to demonstrate its efficiency and performance. The 21 results show that the NLP model can be substituted with the high-speed linear programming model. Moreover, the computation 22 speed is improved by using the BD method. Finally, the network and harmonic indexes improved and charging cost reduced 23 using the proposed idea. 24 25

This paper reviews the most recent and relevant research into the variability characteristics of wind and solar power resources in Europe. The background for this study is that wind and solar resources will probably constitute major components of the future European power system. Such resources are variable, and EU plans to balance the variability with more grids and demand response. Thus, planning for the future power system requires an in-depth understanding of the variability. Resource variability is a multi-faceted concept best described using a range of distinct characteristics, and this review is structured on the basis of seven of these: Distribution Long-Term (hours to years), Distribution Short-Term (less than one hour), Step Changes, Autocorrelation, Spatial Correlation, Cross Correlation and Predictable Patterns. The review presents simulations and empirical results related to resource variability for each of these characteristics. Results to date reveal that the variability characteristics of the future power system is limited understood. This study recommends the development of a scheme for greater systematic assessment of variability. Such a scheme will contribute to the understanding of the impacts of variability and will make it possible to compare alternative power production portfolios and impacts of grid expansions, demand response and storage technologies.