Abstract
This paper presents two contributions developed in the framework of evolvDSO Project to support TSO-DSO cooperation. The Interval Constrained Interval Power Flow (ICPF) tool estimates the flexibility range at primary substations by aggregating the distribution network flexibility. The Sequential Optimal Power Flow (SOPF) tool defines a set of control actions that keep the active and reactive power flow within pre-agreed limits at primary substations level, by integrating different types of flexibility levers. Several study test cases were simulated using data of four real distribution networks from France and Portugal, with different demand/generation profiles and several degrees of flexibility.

Abstract
The growing integration of renewable energy in power systems demands for adequate planning of generation systems not only to meet long-term capacity requirements hut also to cope with sudden capacity shortages that can occur during system operation. As a matter of fact, system operators must schedule an adequate amount of operational reserve to avoid capacity deficits which can be caused by, for instance, overestimating the wind power that will be available. The framework proposed for the long-term assessment of operational reserve relies on the Nave forecasting method to produce wind power forecasts for the next hour. This forecasting model is simple and widely used to obtain short-term forecasts. However, it has been shown that regression models, such as the Autoregressive Integrated Moving Average (ARIMA) model, can outperform the Naive model even for forecasting horizons of up to 1 hour. This paper investigates the differences in the risk indices obtained for the long-term operational reserve when using the Naive and the ARIMA forecasting models. The objective is to assess the impact of the forecasting error in the long-term operational reserve risk indices. Experiments using the Sequential Monte Carlo Simulation (SMCS) method were carried out on a modified version of the IEEE RTS 79 test system that includes wind and hydro power variability. A sensitivity analysis was also performed taking into account several wind power integration scenarios and two different merit orders for scheduling generating units.

Abstract
In this paper, a number of possibilities are presented and discussed for the ownership of distributed storage devices (DSD) in a Smart Grid environment. The cases in which the distribution system operator (DSO) has either full control (grid owned storage) or no control whatsoever over the operation of the DSD (independently owned storage) will be differentiated. For each ownership possibility, the technical and regulatory implications are discussed, with analysis and validation of the results being performed on real MV distribution networks, both rural and urban. In order to evaluate each ownership possibility, a number of multi-period optimization models are presented, corresponding to different assumptions in regards to the operation of the DSD. The resulting daily operation strategies are subsequently used as a basis for carrying out distribution reinforcement planning.

Abstract
The emergence of self-consumption in low voltage consumers has technical and regulatory consequences, due to the changes in the network flows. In this paper these impacts are analysed through a small case study where different production/storage arrangements are considered. The technical analysis shows the voltage profiles' variation and identifies possible overvoltages and the effect of mitigation measures like storage. The regulatory analysis shows that, in order to maintain the remuneration of the Distribution System Operator (DSO) and Transmission System Operator (TSO), network tariffs parameters would change dramatically for the ordinary consumers, unless new rules are defined for the contribution of LV consumers.

Abstract
The current Portuguese Tariff Code dates from December 2014 and requires that the Distribution Network Operators (DSO), submit to the Portuguese Energy Services Regulatory Agency, ERSE, a plan for a pilot experiment and a Cost Benefit Analysis (CBA) regarding the introduction of dynamic options in the Access Tariffs in Portugal. In view of this request, EDP Distribuicao, the main Portuguese DSO, established a contract with INESC TEC to conduct these studies and to prepare a report to submit to ERSE by June 2016. In this scope, this paper reports the results obtained so far namely regarding the CBA analysis. This analysis includes the identification of critical hours during which dynamic tariffs can be activated, the estimate of the impact of demand transfers to adjacent hours on the electricity market Social Welfare Function, on network losses, on the investment network avoided costs due to the possible deferral of reinforcements or expansions and on the costs of contracting reserves. These items were estimated along a period of 15 years and together with the estimate of the implementation costs of dynamic tariffs were used to conduct the mentioned CBA analysis.

Abstract
A considerable number of classic and modern control applications in distribution systems are developed aiming at make the most of the existing infrastructure. Under this perspective, investments postponement in grid upgrade appears as a good expectable result. The advent of smart grids enhances this expectation since it promises ubiquitous system monitoring, secure and trustworthy communication technologies and advanced control schemes. These features will allow the implementation of innovative algorithms for better operation and management of system assets. New possibilities arise for DSM, microgeneration control, electric vehicle charging and intelligent operation of energy storage devices. The scientific literature has countless examples that illustrate the benefits of such tools. A frequent outcome of these studies highlights the advantage of investments deferral in network reinforcement. This paper analyzes the combined effects of these control actions with the investments required for network upgrade, namely in lines and transformers reinforcement. Contrary to other research papers, our results demonstrate that investments deferral could lead frequently to higher costs in a long-term perspective.