Abstract
Integration of aggregated demand response into the wholesale electricity market is an emerging field of research. Contrary to conventional service providers, most of the demand side participants act voluntarily. However, due to wholesale market regulations, reliable and effective participation of huge numbers of customers is a vital task for aggregators. The existing retail programs aim to motivate customers to take part in events in return for static or individual performance-based incentives. These programs do not focus on engaging customers to act in a collaborative way and therefore have limited effectiveness. This study proposes a novel retail demand response program in which the incentives are dependent on the aggregated performance of participants. Considering the existing wholesale and retail market structures together with demand response aggregator responsibilities, an adaptable program is developed for more effective performance and indirect collaboration of customers. The contribution of the program is compared with a number of different DR programs adopting concepts from game theory.

Abstract
In restructured power systems, the adequacy of the transmission network may be defined as the ability to meet reasonable demands by transmission of electricity (as stated by the Directive 2009/72/EC). The symmetric/constrained fuzzy power flow (CFPF) was recently proposed as a suitable tool to quantify that adequacy. In this paper, the use of the symmetric fuzzy power flow/CFPF is extended to support the decision process of investment in network components to accomplish a specific adequacy criteria. A technique based on dual variables, obtained from the linear formulation of the CFPF, is used. The importance of the duality information concerning the adequacy indices is explained. The proposed methodology is applied on IEEE 14 bus reliability test system to demonstrate its applicability. Copyright © 2017 John Wiley & Sons, Ltd.

Abstract
The symmetric/constrained fuzzy power flow (SFPF/CFPF) models are suitable to quantify the adequacy of transmission network in satisfying “reasonable demands for the transmission of electricity” as defined, in the European Directive 2009/72/EC. In this paper, SFPF/CFPF is mainly used to identify the basic repressions (inappropriate definition of reasonable demands) of fuzzy data (generation or load) when the adequacy of a transmission system is assessed. This situation arises essentially in cases where the network configuration does not fully support the requested power specifications. It means that these requests are inadequately formulated and lead to the creation of artificial repression in the results (artificial inadequacy of the transmission system). In this article, it is intended to show how these cases can be identified. For this purpose, the SFPF will be used, which does not consider branch limits. With this study, it is also shown how the reference power flows of the system are obtained in order to identify the congested branches.

Abstract
This paper analyzes the implementation of new technologies in network industries through the development of a suitable regulatory scheme. The analysis focuses on Smart Grid (SG) technologies which, among others benefits, could save operational costs and reduce the need for further conventional investments in the grid. In spite of the benefits that may result from their implementation, the adoption of SGs by network operators can be hampered by the uncertainties surrounding actual performances. A decision model has been developed to assess the firms' incentives to invest in "smart" technologies under different regulatory schemes. The model also enables testing the impact of uncertainties on the reduction of operational costs, and of conventional investments. Under certain circumstances, it may be justified to support the development and early deployment of emerging innovations that have a high potential to ameliorate the efficiency of the electricity system, but whose adoption faces many uncertainties.

Abstract
The design of efficient and high power density electrical machines needs an accurate characterization of magnetic phenomena. Core losses estimation is usually addressed by empirical models, where its lack of accuracy is well known. Hysteresis models are able to take an insight into the magnetic physical mechanisms. Compared to the empirical models, they contribute to a higher accuracy in modeling electromagnetic systems, including core losses estimation. At a macroscopic level, two models are often used: the Preisach and the Jiles-Atherton (J-A) models. This paper presents their basic formulation, as well the main limitations and scope of application. This is a first step to investigate the possible application of hysteresis models, in order to reach accurate core losses estimation in switched reluctance machines.

Abstract
Unknown input observers (UIO) can be used in the model-based fault diagnosis (FD) system to reduce or eliminate the effect of unknown disturbances present on the process and used to create a set of residuals that are decoupled and sensitive to faults. In this work, a new FD scheme of the In-Wheel motors electric vehicle (IWM-EV) with active front steering was carried out, as well as the design of the fault isolation banks of UIOs. These banks are used to generate residuals that are robust againts to noise and are sensitive to only one fault. This way the faults in the steering or in-wheel actuator are detected and isolated with a higher rate of accuracy. The proposed FD scheme is verified by Carsim® and Matlab/Simulink® cosimulation. © 2017 Taylor & Francis Group, London.