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
In the smart grid environment, reserve services (RS) are also expected from the demand side, taking into account the flexibility and availability of loads connected into the grid. This paper proposes a method to calculate the availability of thermal domestic loads for the provision of upward RS, considering some aspects regarding the constructive characteristics of the appliances, as well as the consumer habits and comfort preferences. A case study comprising 500 consumers with three types of domestic thermal loads (electric water heaters, air-conditioners, and refrigerators) will be used to illustrate the method.

Abstract

Abstract
The smart grid concept increases the observability and controllability of the distribution system, which creates conditions for bi-directional control of Distributed Energy Resources (DER). The high penetration of Renewable Energy Resources (RES) in the distribution grid may create technical problems (e.g., voltage problems, branch congestion) in both transmission and distribution systems. The flexibility from DER can be explored to minimize RES curtailment and increase its hosting capacity. This paper explores the use of the Monte Carlo Simulation to estimate the flexibility range of active and reactive power at the boundary nodes between transmission and distribution systems, considering the available flexibility at the distribution grid level (e.g., demand response, on-load tap changer transformers). The obtained results suggest the formulation of an optimization problem in order to overcome the limitations of the Monte Carlo Simulation, increasing the capability to find extreme points of the flexibility map and reducing the computational effort.