Abstract
Este relatório corresponde ao trabalho realizado pela Universidade Aberta no âmbito do contrato estabelecido com a FCT/FCCN para a elaboração de uma proposta de Matriz Técnico-Pedagógica inicial para a plataforma NAU, destinada a cursos online, massivos e abertos (MOOC). Segue a estrutura apresentada no caderno de encargos da entidade adjudicante.

Abstract
This paper presents a novel analytic method to uniquely solve inverse kinematics of 7 degrees-of-freedom manipulators while avoiding joint limits and singularities. Two auxiliary parameters are introduced to deal with the self-motion manifolds: the global configuration (GC), which specifies the branch of inverse kinematics solutions; and the arm angle (psi) that parametrizes the elbow redundancy within the specified branch. The relations between the joint angles and the arm angle are derived, in order to map the joint limits and singularities to arm angle values. Then, intervals of feasible arm angles for the specified target pose and global configuration are determined, taking joint limits and singularities into account. A simple metric is proposed to compute the elbow position according to the feasible intervals. When the arm angle is determined, the joint angles can be uniquely calculated from the position-based inverse kinematics algorithm. The presented method does not exhibit the disadvantages inherent to the use of the Jacobian matrix and can be implemented in real-time control systems. This novel algorithm is the first position-based inverse kinematics algorithm to solve both global and local manifolds, using a redundancy resolution strategy to avoid singularities and joint limits.

Abstract
Electric vehicle (EV) technology with a vehicle to grid (V2G) property is used in power systems to mitigate greenhouse gas emissions, reduce peak load of the distribution system, provide ancillary service, etc. In addition, demand response (DR) programs as an effective strategy can provide an opportunity for consumers to play a significant role in the planning and operation of a smart distribution company (SDISCO) by reducing or shifting their demand, especially during the on-peak period. In this paper, the optimal operation of a SDISCO is evaluated, including renewable energy resources (RERs) along with EV parking lots (PLs). RER and PL uncertainties and a suitable charging/discharging schedule of EVs are also considered. Furthermore, price-based DR programs and incentive-based DR programs are used for operational scheduling. To achieve this aim, a techno-economic formulation is developed in which the SDISCO acts as the owner of RERs and PLs. Moreover, DR programs are prioritized by using the technique for order preference by similarity to ideal solution method. In addition, a sensitivity analysis is carried out to investigate different factors that affect the operational scheduling of the SDISCO. The proposed model is tested on the IEEE 15-bus distribution system over a 24-h period, and the results prove the effectiveness of the model.

Abstract

Abstract
In the optimal and economic operation of the power system, generation scheduling is an essential task. Conventional short-term generation scheduling does not regard the huge important operational issues related to the generators, such as initial enterprise costs, maintenance costs, fuel availability, monthly load, etc. Hence, due to the time horizon scheduling of the daily short-term generation scheduling, it is not optimal in the long-term operation while considering the mentioned effects. In this context, this paper proposes a stochastic higher level of scheduling named Stochastic Mid-Term Generation Scheduling of Wind-Thermal systems by considering fixed and variable maintenance costs of generators units. In the proposed model, the 2m + 1 Point Estimate Method is applied to accurately evaluate the uncertainty related to the operation cost wind power and the load uncertainties for the proposed problem. To effectively solve it, a heuristic algorithm named Adaptive Modified Cuckoo Search Algorithm is employed with a novel self-adaptive Wavelet mutation tactic. To assess the performance of the proposed algorithm on solving the problem, the results are compared with the latest algorithms presented in the literature. Numerical results confirm the efficiency and superiority of the 2m + 1 point estimate method model and stability of the novel adaptive modified cuckoo search algorithm on solving the stochastic mid-term generation scheduling of wind-thermal systems problem.

Abstract
In this work we address the problem of switching the shape of a formation of undistinguishable nonholonomic mobile robots. Each agent moves from the current to its target oriented position using the shortest path. We combine results from previous work on optimal formation switching when the agents are holonomic with results on the structure of the shortest path for nonholonomic agents.