In recent years, there has been an increase of Renewable Energy Sources (RES) in energy markets that has to lead their agents to become more proactive. In this scenario, a market structure based on Peer-to-Peer (P2P) transactions is very promising but presents challenges for the network operation. A critical challenge is to ensure that network constraints are not violated due to energy trades between peers and neither due to the use of reserve capacity. In this paper, it is proposed a new iterative sequential approach for energy and reserve P2P market that ensures the feasibility of both energy and reserve transactions under network constraints. The methodology considers the interaction between the prosumers and the Distribution System Operator (DSO) in making the final market/operation decision and can be integrated into the existing distribution system. The proposed approach includes the estimation of reserve requirements based on the RES uncertain behavior from historical generation data, which allows identifying RES patterns. The proposed model is assessed through a case study that uses a 14-bus system, under the technical and economic criteria. The results show that the approach can ensure a feasible network operation encompassing energy and reserve markets.

Considering the Brazilian energy policy's future, the perspective of a more decentralized energy system must be accounted for in the face of technological, business, and energy matrix changes. Therefore, the prosumer's figure combined with new Business Models (BM) brings opportunities and challenges for the sector. This paper aims to solidify knowledge, identify and understand the main regulatory barriers and enablers for the development of prosumers and prosumer-driven BMs in the Brazilian energy market. A comprehensive review of existing regulations provides a starting point for improving the relevant legal frameworks for prosumers' aggregation. Then, an analysis of innovative BMs in the Brazilian regulatory framework is carried out, seeking to guide the decisions for the country to develop its political and regulatory environment in the future. The paper concludes with policy recommendations to promote prosumers aggregation in the Brazilian energy sector. We conclude that the main barriers to prosumers' integration are of regulatory and technological nature, and the exploration of innovative BMs is crucial for the sector development. Redefining the role and responsibilities of utilities is a key factor, together with exploring collective self-consumption.

The wind farm layout optimization problem consists of determining the optimal configuration with the objectives of maximizing the extracted power while minimizing the costs related to the project. The present work aims at comparing the performance of the computational intelligence techniques named bat algorithm, grey wolf optimizer, and sine cosine algorithm, considering different wind direction scenarios and the probabilities of occurrence of such scenarios under analysis. The methodologies employed consider the wind weakening effect to determine the number and positions of the wind turbines in an offshore wind farm. A case study from the literature is used to evaluate the methodologies employed with the representation of different wind direction scenarios.

This paper proposes a two-stage framework to solve the long-term transmission network expansion planning (TNEP) problem ensuring user-defined reliability levels and wind curtailment over the planning horizon. In the first stage, the static TNEP (S-TNEP) problem is solved to define where a set of new lines must be installed at the end of planning horizon. In the second stage, a multistage procedure is performed to solve the dynamic TNEP (D-TNEP) in order to determine the moment that each transmission line should be built. Both S-TNEP and D-TNEP are decomposed into investment decision and performance assessment through a bi-level scheme based on Benders decomposition; thus, the reliability is considered and evaluated over the planning process. The reliability and performance indexes are obtained through the non-chronological Monte Carlo simulation considering the random behavior of transmission lines failures, load fluctuations and uncertainties over wind availability. The loss of wind probability performance index is introduced to measure the probability of wind curtailment in each connection point of the system, and it is used to prevent wind farms from being underused. The proposed methodology is tested in modified versions of the 24-bus IEEE reliability test system and the IEEE 118-bus test system.

This chapter presents applications of the bio-inspired metaheuristic known as monkey search (MS) to the planning of electrical energy distribution systems (EEDS). The technique is inspired by the behavior of a monkey searching for food in a jungle through movements of climbing trees. In this sense, an artificial tree has levels that contain candidate solutions for an optimization problem, in analogy with food sources at a given level of a real tree. The search in an artificial tree begins from a single candidate solution that is considered as its root at the first level. From the root, two other nodes or candidate solutions of the next level are derived through single changes, and this procedure is followed for obtaining all levels, i.e., each node in a given level is obtained from a change in another node at the previous level. The total number of levels is a parameter of the method called the height of the tree. The best candidate solutions found during the search in an artificial tree are updated and stored in an adaptive memory to aid the optimization process in finding promise routes for attractive nodes. The algorithm applied for the planning of energy distribution systems, called modified monkey search (MMS), is an improvement of the original MS method with the purpose of a better fit to the EEDS applications. The planning problems covered by the MMS application are the optimal allocation of fixed and switched capacitor banks, as well as diverse kind of meters as phasor measurement units and smart meters to aid the system state estimation process. Previous results of such applications have shown the potential and effectiveness of the MMS applied for planning EEDS.

This chapter presents an adapted bat-inspired algorithm (ABA) besides a search space shrinking (SSS) in the frame of an efficient hybrid algorithm (EHA) for transmission network expansion planning (TEP). The network losses considered in the comprehensive efficient application of EHA to a real system with large-scale. In this approach, ABA handles the discrete variables of TEP. The evaluation of the fitness function as well as the planning options are via an optimal power flow. The SSS technique has a crucial role in the definition of ABA initial candidates, thereof considerably reduction of solution search space, thus the computational performance of the proposed ABA. The evaluation of Southern Brazilian system validates the proposed approach in comparison to the other state-of-the-art algorithms.

This work presents an efficient hybrid algorithm (EHA) that consists of a search space reducer (SSR) and a modified bat-inspired algorithm (MBA) to solve the transmission network expansion planning (TNEP). The contribution of the proposal is to consider, at the same time, the security constraints criterion ‘N − 1’, load scenarios and network losses to give a more comprehensive approach in an efficient manner, which allows applying the EHA to large-scale real system. Discrete variables in the TNEP are handled by the MBA, and an optimal power flow is used to evaluate the fitness function as well as planning options. By using the SSR to define the initial candidate set for the MBA, the solution search space is reduced improving the computational performance of the proposed MBA. To validate the proposed method and show its efficiency in comparison with others in the literature, tests are conducted on Garver and IEEE 24-bus test system, in addition to an equivalent Brazilian system.

The gene (xylA) coding for the Lactobacillus brevis xylose isomerase (Xi) has been isolated and its complete nucleotide sequence determined. L. brevis Xi was purified and the N-terminal sequence determined. All attempts to directly clone the intact xylA using a degenerative primer deduced from amino acids (aa) 10-14 were not successful. A fragment coding for the first 462 bp from the 5' end of xylA was isolated by PCR with two primers, one coding for aa M36 to W43 and the second coding for an aa sequence (WGGREG) conserved in a number of Xi's isolated from other bacteria. From the sequence of this fragment, two additional PCR primers were synthesized, which were used in an 'outward' reaction to clone a 546-bp fragment including a region upstream from the N terminus. Finally, the complete xylA gene was cloned in a 0.43-kb NlaIII-SalI fragment and a 1.9-kb SalI-EcoRI fragment. The 449-aa sequence for the L. brevis Xi shows homology with Xis isolated from other bacteria, especially within the primary catalytic domains of the enzyme.