Simulation and optimization model for the construction of electrical substations

One of the most complex construction projects is electrical substations. An electrical substation is an auxiliary station of an electricity generation, transmission and distribution system where voltage is transformed from high to low or the reverse using transformers. Construction of electrical substation includes civil works and electromechanical works. The scope of civil works includes construction of several buildings/components divided into parallel and overlapped working phases that require variety of resources and are generally quite costly and consume a considerable amount of time. Therefore, construction of substations faces complicated time-cost-resource optimization problems. On another hand, the construction industry is turning out to be progressively competitive throughout the years, whereby the need to persistently discover approaches to enhance construction performance. To address the previously stated afflictions, this dissertation makes the underlying strides and introduces a simulation and optimization model for the execution processes of civil works for an electrical substation based on database excel file for input data entry. The input data include bill of quantities, maximum available resources, production rates, unit cost of resources and indirect cost. The model is built on Anylogic software using discrete event simulation method. The model is divided into three zones working in parallel to each other. Each zone includes a group of buildings related to the same construction area. Each zone-model describes the execution process schedule for each building in the zone, the time consumed, percentage of utilization of equipment and manpower crews, amount of materials consumed and total direct and indirect cost. The model is then optimized to mainly minimize the project duration using parameter variation experiment and genetic algorithm java code implemented using Anylogic platform. The model used allocated resource parameters as decision variables and available resources as constraints. The model is verified on real case studies in Egypt and sensitivity analysis studies are incorporated. The model is also validated using a real case study and proves its efficiency by attaining a reduction in model time units between simulation and optimization experiments of 10.25% and reduction in total cost of 4.7%. Also, by comparing the optimization results by the actual data of the case study, the model attains a reduction in time and cost by 13.6% and 6.3% respectively. An analysis to determine the effect of each resource on reduction in cost is also presented

Data-Intensive Computing in Smart Microgrids

Microgrids have recently emerged as the building block of a smart grid, combining distributed renewable energy sources, energy storage devices, and load management in order to improve power system reliability, enhance sustainable development, and reduce carbon emissions. At the same time, rapid advancements in sensor and metering technologies, wireless and network communication, as well as cloud and fog computing are leading to the collection and accumulation of large amounts of data (e.g., device status data, energy generation data, consumption data). The application of big data analysis techniques (e.g., forecasting, classification, clustering) on such data can optimize the power generation and operation in real time by accurately predicting electricity demands, discovering electricity consumption patterns, and developing dynamic pricing mechanisms. An efficient and intelligent analysis of the data will enable smart microgrids to detect and recover from failures quickly, respond to electricity demand swiftly, supply more reliable and economical energy, and enable customers to have more control over their energy use. Overall, data-intensive analytics can provide effective and efficient decision support for all of the producers, operators, customers, and regulators in smart microgrids, in order to achieve holistic smart energy management, including energy generation, transmission, distribution, and demand-side management. This book contains an assortment of relevant novel research contributions that provide real-world applications of data-intensive analytics in smart grids and contribute to the dissemination of new ideas in this area

Secure data sharing in cloud computing: a comprehensive review

Cloud Computing is an emerging technology, which relies on sharing computing resources. Sharing of data in the group is not secure as the cloud provider cannot be trusted. The fundamental difficulties in distributed computing of cloud suppliers is Data Security, Sharing, Resource scheduling and Energy consumption. Key-Aggregate cryptosystem used to secure private/public data in the cloud. This key is consistent size aggregate for adaptable decisions of ciphertext in cloud storage. Virtual Machines (VMs) provisioning is effectively empowered the cloud suppliers to effectively use their accessible resources and get higher benefits. The most effective method to share information resources among the individuals from the group in distributed storage is secure, flexible and efficient. Any data stored in different cloud data centers are corrupted, recovery using regenerative coding. Security is provided many techniques like Forward security, backward security, Key-Aggregate cryptosystem, Encryption and Re-encryption etc. The energy is reduced using Energy-Efficient Virtual Machines Scheduling in Multi-Tenant Data Centers

Intelligent Data Storage and Retrieval for Design Optimisation – an Overview

This paper documents the findings of a literature review conducted by the Sir Lawrence Wackett Centre for Aerospace Design Technology at RMIT University. The review investigates aspects of a proposed system for intelligent design optimisation. Such a system would be capable of efficiently storing (and compressing if required) a range of types of design data into an intelligent database. This database would be accessed by the system during subsequent design processes, allowing for search of relevant design data for re-use in later designs, allowing it to become very efficient in reducing the time for later designs as the database grows in size. Extensive research has been performed, in both theoretical aspects of the project, and practical examples of current similar systems. This research covers the areas of database systems, database queries, representation and compression of design data, geometric representation and heuristic methods for design applications.

Telecommunication Systems

This book is based on both industrial and academic research efforts in which a number of recent advancements and rare insights into telecommunication systems are well presented. The volume is organized into four parts: "Telecommunication Protocol, Optimization, and Security Frameworks", "Next-Generation Optical Access Technologies", "Convergence of Wireless-Optical Networks" and "Advanced Relay and Antenna Systems for Smart Networks." Chapters within these parts are self-contained and cross-referenced to facilitate further study