Abstract
This paper addresses the problem of decision making in Unit Commitment in systems with a significant penetration of wind power. Traditional approaches to Unit Commitment are inadequate to fully deal with the uncertainties associated to wind, represented by scenarios of forecasted wind power qualified by probabilities. Departing from a critique of planning paradigms, the paper argues that a stochastic programming approach, while a step in the good direction, is insufficient to model all aspects of the decision process and therefore proposes the adoption of models based on a Risk Analysis paradigm. A case study is worked out reinforcing this perspective. In a multi-objective context, the properties of the cost vs. risk Pareto-optimal fronts are analyzed, where risk may be represented by aversion to a worst scenario or a worst event. It is shown that the Pareto-optimal front may not be convex, which precludes a simplistic use of tradeoff concepts. It is also shown that decisions based on stochastic programming may in fact put the system at risk. An evaluation of risk levels and cost of hedging against undesired events is proposed as the paradigm to be followed in Unit Commitment decision making. (C) 2016 Published by Elsevier Ltd.

Abstract
The increase of demand side participation in reserve service (RS) requires the extension of the markets' activity to the millions of consumers present in the residential sector. This paper proposes a method that performs a bottom-up aggregation of residential demand-side flexibility associated with domestic appliances, namely Thermostatically Controlled Loads (TCL). The flexibility profiles provided by each residential consumer are transformed into aggregated reserve bids to be offered in the day ahead tertiary reserve markets. A case study involving 1500 end-users associated with an aggregator bidding in the Portuguese tertiary reserve market will be used to illustrate the method. (C) 2016 Published by Elsevier B.V.

Abstract
The integration of wind power in electricity generation brings new challenges to the unit commitment problem, as a result of the random nature of the wind speed. The scheduling of thermal generation units at the day-ahead stage is usually based on wind power forecasts. Due to technical limitations of thermal units, deviations from those forecasts during intra-day operations may lead to unwanted consequences, such as load shedding and increased operating costs. Wind power forecasting uncertainty has been handled in practice by means of conservative stochastic scenario-based optimization models, or through additional operating reserve settings. However, generation companies may have different attitudes towards the risks associated to wind power variability. In this paper, operating costs and load shedding are modeled by non-linear utility functions aggregated into a single additive utility function of a multi-objective model. Computational experiments have been done to validate the approach: firstly we test our model for the wind-thermal unit commitment problem and, in a second stage, pumped storage hydro units are added, leading to a model with wind-hydro-thermal coordination. Results have shown that the proposed methodology is able to correctly reflect different risk profiles of decision makers for both models.

Abstract
This paper evaluates the flexibility provided by distributed energy resources (DER) in a real electricity distribution network in Germany. Using the Interval Constrained Power Flow (ICPF) tool, the maximum range of flexibility available at the primary substation was obtained for different operation scenarios. Three test cases were simulated, differing mainly in the considered level of renewable energy sources (RES) production. For each test case, the obtained results enabled the construction of flexibility areas that define, for a given operating point, the limits of feasible values for the active and reactive power that can be exchanged between the TSO and the DSO. Furthermore, the tool can also be used to evaluate the contribution from each type of DER to the overall distribution network flexibility.

Abstract

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.