Multi-Tier Stack of Block Chain with Proxy Re-Encryption Method Scheme on the Internet of Things Platform

Block chain provides an innovative solution to information storage, transaction execution, security, and trust building in an open environment. The block chain is technological progress for cyber security and cryptography, with efficiency-related cases varying in smart grids, smart contracts, over the IoT, etc. The movement to exchange data on a server has massively increased with the introduction of the Internet of Things. Hence, in this research, Splitting of proxy re-encryption method (Split-PRE) has been suggested based on the IoT to improve security and privacy in a private block chain. This study proposes a block chain-based proxy re-encryption program to resolve both the trust and scalability problems and to simplify the transactions. After encryption, the system saves the Internet of Things data in a distributed cloud. The framework offers dynamic, smart contracts between the sensor and the device user without the intervention of a trustworthy third party to exchange the captured IoT data. It uses an efficient proxy re-encryption system, which provides the owner and the person existing in the smart contract to see the data. The experimental outcomes show that the proposed approach enhances the efficiency, security, privacy, and feasibility of the system when compared to other existing methods.

A Block-Chain based Framework for Educational Domain and its Benefits

A chain of blocks that contains information is the definition of Blockchain. The technique is intended to timestamp digital documents so that it is not possible to temper them. The purpose of blockchain is to solve the double records problem without the need of a central server. Blockchain provides a creative approach to storing information, executing transactions, conducting tasks and trust building. Blockchain is an emerging technology for the applications Smart Cities, Smart Grids, Healthcare, Education, Crypto-currency and Supply chain. This research work would offer a detailed analysis of Blockchain in the Educational domain. It also studies the various applications of Blockchain technology. Keywords: Blockchain, Smart Cities, Healthcare, Education, Supply Chain, Privacy, Security.

Aquila Optimization Based Harmonic Elimination in a Modified H-Bridge Inverter

Multilevel inverters (MLIs) are capable of producing high-quality output voltage and handling large amounts of power. This reduces the size of the filter while also simplifying the circuitry. As a result, they have a wide range of applications in industries, particularly in smart grids. The input voltage boosting feature is required to use the MLI with renewable energy. Moreover, many components are required to get higher output voltage levels that add weight and cost to the circuit. Numerous MLI topologies have been identified to minimize the losses, device count, and device ratings. A seven-level modified H-bridge inverter with a reduced component count, and reduced THD is presented in this paper. Two DC sources with six IGBTs have been used to generate a seven-level output voltage, and the Aquila Optimizer (AO) has been implemented to get the regulated output. MATLAB/Simulink environment has been used for designing the simulation model. Furthermore, the simulation result has been validated in the laboratory on a hardware setup using the DSP-TMS320F28335 Launchpad. With the reduced number of switching devices as well as the dc supply, the size of the inverter is compacted and becomes more economical.

SMART GRIDS COMO ALTERNATIVA DE DESENVOLVIMENTO URBANO INTELIGENTE E SUSTENTÁVEL EM PARINTINS/AM

Devido à rápida e não planejada urbanização surgem problemas de aclimatação urbana, para os quais alternativas de soluções foram desenvolvidas a partir do conceito de Smart City. Nesta pesquisa, o foco é nos problemas da gestão da produção e da distribuição de energia elétrica em Parintins/AM. Para a problemática energética são utilizados os conceitos de rede elétrica inteligente, Smart Grid, que por meio da tecnologia otimiza os sistemas de produção e distribuição de energia, tornando-os mais eficientes, eficazes e sustentáveis. O objetivo deste trabalho é analisar, com base nas teorias desenvolvidas acerca das Smart Cities e das Smart Grids, quais são os aspectos que devem ser levados em consideração para a gestão inteligente e sustentável da produção e distribuição de energia elétrica em Parintins/AM. O paradigma de pesquisa é o funcionalista, por meio de pesquisa qualitativa, com delineamento descritivo e analítico. Os dados foram levantados por meio de revisão bibliográfica, análise documental e entrevistas semiestruturadas, triangulados e analisados mediante técnica de análise de conteúdo. Os resultados obtidos foram: 1) desenvolvimento científico na área das Smart Cities e Smart Grids, em construção, por meio de estudo empírico no interior do Amazonas; 2) identificação dos fatores impulsionadores e limitantes à implantação de Smart Grids em Parintins/AM.

Integrative Smart Grids’ Assessment System

The COVID-19 pandemic has significantly affected the energy sector. The new behavior of industrial and non-commercial consumers changes the energy consumption model. In addition, the constraints associated with the coronavirus crisis have led to environmental effects from declining economic activity. The research is based on evidence from around the world showing significant reductions in emissions and improved air quality. This situation requires rethinking the energy development strategy, particularly the construction of smart grids as a leading direction of energy development. Evaluating the efficiency of smart grids is a vital tool for disseminating successful experience in improving their management. This paper proposes an approach to a comprehensive assessment of smart grids based on a comparative analysis of existing methods, taking into account the changes that need to be considered after the experience gained from the COVID-19 pandemic. The approach provides an accurate set of efficiency indicators for assessing smart grids to account for the direct and indirect effects of smart grids’ implementation. This evaluation approach can be helpful to policymakers in developing energy efficiency programs and implementing energy policy.

Um Estudo Comparativo do Desempenho de Algoritmos para a Reconfiguração de Rede Elétrica

Smart grids (SGs) have as one of their basic proposals to incorporate intelligence into the electric grid through computing and communication technologies aiming at greater efficiency and effectiveness in their operation and control. Power loss, quality, and failures are inherent in the generation process, transmission, and distribution of electricity and, in the context of SGs, should be minimized to ensure greater resilience and system efficiency. Dynamic and efficient distribution network reconfiguration is an example of an SG functionality. The reconfiguration process consists of adjusting or changing the topology of the distribution network from the opening and closing of switches to minimize technical losses, optimize operating parameters, and restore power supply in contingency situations. The nature of the network reconfiguration problem is combinatorial, complex, and non-linear. Aiming to minimize convergence time in search of a solution in medium and large topologies, heuristic and optimization techniques are an alternative. This dissertation proposes a new genetic algorithm, GAEnhanced (Genetic Algorithm Enhanced), to solve network reconfiguration and make a comparative study of performance aspects of this algorithm in relation to other solutions and algorithmic strategies used. The main goal is to evaluate the algorithm implementation strategies for dynamic reconfiguration and on-the-fly distribution networks from a broader perspective, in addition to proposing a new solution with the GAEnhanced algorithm. A simulator (DNRSim) with basic functionalities for implementation and tests of network reconfiguration algorithms for the Smart Grid was developed within the scope of this dissertation. The comparative study of the performance of the GAEnhanced algorithm and other solutions with the DNRSim uses the IEEE models for system tests (14-bus, 30-bus, 57-bus, 118-bus, and 330-bus). The comparative study results illustrate the different ways to efficiently compute network reconfiguration solutions (scalability, time, and quality) and demonstrate the feasibility of using the GAEnhanced algorithm in the context of Smart Grids in a perspective of deploying more autonomic and intelligent solutions.