Paulo Moisés

Abstract
To modernize distribution networks and enable the energy transition, we need to understand the most appro-priate regulatory approach. A set of new technologies with positive externalities challenge the traditional reg-ulatory models. We develop a decision model to assess firms' incentives to invest in new technologies under different regulatory schemes that consider externality effects. Results show that regulatory schemes under which companies retain the gains (or losses) of achieving (or not) efficiency targets more effectively promote inno-vation investments that reduce network costs. However, a case-by-case approach should be preferred for tech-nologies whose benefits go mostly beyond the network activities.

Abstract
The planning of the transmission network is an issue that, over the years, has received much attention, particularly due to the impact that this infrastructure has on the safe and reliable functioning of electrical systems. The search for solutions addressing climate change has led to several changes in the functioning of electrical systems, particularly concerning the increasing integration of renewable electricity production. However, in recent years, changes in the load side of the electrical system have also emerged. In particular, electric mobility has been developing, and a high penetration of electric vehicles (EVs) is expected in near future. This consumption is supplied by the distribution system but will impact the transmission network. Naturally, the amount of energy used by EVs is subject to uncertainties, which makes the problem complex. Those uncertainties cannot be easily modeled using statistical distributions because of the reduced history of available information. The transmission system operator (TSO) needs an efficient tool to analyze the adequacy of the transmission network to supply the distribution networks with high penetration of EVs. In this paper, a methodology based on symmetric/constrained fuzzy power flow is proposed to find the optimal investment policy at the transmission level while satisfying the technical constraints. The concept of dual variables provided by Lagrange multipliers, the natural result of the nonlinear optimization problem, is used to obtain the most promising reinforcement options considering the actual structure of the transmission network. The proposed model is tested on an IEEE 14-bus system.

Abstract
A hybrid population-based metaheuristic, Hybrid Canonical Differential Evolutionary Particle Swarm Optimization (hC-DEEPSO), is applied to solve Security Constrained Optimal Power Flow (SCOPF) problems. Despite the inherent difficulties of tackling these real-world problems, they must be solved several times a day taking into account operation and security conditions. A combination of the C-DEEPSO metaheuristic coupled with a multipoint search operator is proposed to better exploit the search space in the vicinity of the best solution found so far by the current population in the first stages of the search process. A simple diversity mechanism is also applied to avoid premature convergence and to escape from local optima. A experimental design is devised to fine-tune the parameters of the proposed algorithm for each instance of the SCOPF problem. The effectiveness of the proposed hC-DEEPSO is tested on the IEEE 57-bus, IEEE 118-bus and IEEE 300-bus standard systems. The numerical results obtained by hC-DEEPSO are compared with other evolutionary methods reported in the literature to prove the potential and capability of the proposed hC-DEEPSO for solving the SCOPF at acceptable economical and technical levels.

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.