This document proposes an energy management system for a smart microgrid using a multi-objective grey wolf optimization algorithm. The goals are to maximize the use of local renewable energy generation, minimize consumer energy costs, and reduce greenhouse gas emissions. It describes energy controllers that would manage energy sharing between providers and customers. The multi-objective grey wolf optimization technique is said to provide faster optimization than other methods. Simulation results reportedly show reductions in both pollution and energy consumption costs with this approach.
ENERGY MANAGEMENT SYSTEM IN MICROGRID: A REVIEWIRJET Journal
This document provides a review of energy management systems in microgrids. It discusses how energy management systems can help integrate renewable energy resources and reduce greenhouse gas emissions from fossil fuel power generation. The review classifies different approaches to energy management, including control strategies for emissions reduction, energy storage optimization techniques, and methods for reducing energy costs. It also examines demand response management strategies to encourage local power consumption from renewable sources. The document concludes by stating this review provides direction for future research in microgrid energy management.
The document discusses environmental/economic scheduling of renewable energy resources in a micro-grid. It proposes a multi-objective framework to minimize the total operation cost and emission from generating units. Lexicographic optimization and a hybrid augmented-weighted epsilon-constraint method are used to solve the multi-objective optimization problem and generate Pareto optimal solutions. The decision making process uses a fuzzy technique. Case studies show the proposed method improves solutions for cost, emission, and execution time compared to other methods.
Review on Optimization of Microgrid Using Various Optimization TechniquesIJAEMSJORNAL
The development of a smart grid includes the microgrid. Microgrids are essential to the development of the present and future electricity networks, as they can provide many advantages to the expanding and complex power systems, such as better power quality, increased integration of clean and renewable energy sources, increased efficiency, and increased network stability and reliability., etc. It is basically a small power system which has distributed energy resources (like renewable energy etc.). This paper conducts a literature review on Optimization Algorithms of Microgrid. We provide a summary of the typical system structure, which consists of energy end users, energy distribution systems, energy storage systems, and energy generation systems. Finally, we identify areas for future microgrid research challenges.
This document proposes a multi-objective framework for short-term scheduling of a microgrid considering cost minimization and emission minimization objectives. It formulates the problem as a mixed integer nonlinear program with constraints including power balance and unit generation limits. The Normal Boundary Intersection method is employed to solve the multi-objective problem and generate a Pareto front of optimal solutions. Simulation results are presented comparing the proposed approach to other methods.
This document presents a strategic design optimization model for microgrids with multiple energy storage technologies and demand response aggregation. The model (1) uses game theory to model the strategic behavior of utilities, aggregators, and consumers, (2) determines optimal tradeoffs between power imported from the grid and demand response resources, and (3) allocates various storage technologies cost-optimally. The model was tested on a 100% renewable energy microgrid in New Zealand, reducing lifetime costs by an estimated 21% compared to a business-as-usual approach without demand response.
Design and Control Issues of Microgrids : A SurveyIRJET Journal
This document summarizes key issues in the design and control of microgrids. It begins by defining microgrids and outlining their basic design considerations, which include suitable sizing and positioning of distributed energy resources. The document then discusses design aspects like optimal component selection and control strategies. It describes the hierarchical control approach for microgrids, with primary control focusing on voltage/frequency regulation, secondary on deviation mitigation, and tertiary on economic optimization. Finally, it outlines some major issues in microgrid design and control, specifically islanding detection challenges and non-detection zones, where changes in voltage and frequency may not trigger detection.
Interconnecting industrial multi-microgrids using bidirectional hybrid energy...IJECEIAES
Sharing and exchange energy among nearby industrial microgrids are crucial, especially with high energy requirements for their production targets and costly energy storage systems that may be oversized for their operations. Facilitating energy exchange can provide an economic advantage for industrial production by utilizing cheaper energy sources and reducing production costs. This manuscript presents an efficient approach for transferring large energy packets with minimal energy losses using
high-voltage direct current (HVDC) energy transmission. The manuscript methodology focuses on implementing an industrial multi-microgrid using a modular multilevel converter. This converter utilizes two power link channels: a three-phase AC and an HVDC link, creating a hybrid energy transmission between microgrids. When a substantial amount of energy to transfer, the HVDC method enhances overall efficiency by reducing copper losses and mitigating issues associated with the AC link, such as harmonics and skin effects. The modular multilevel converter topology offers high flexibility and the use of fewer converters. Additionally, the HVDC link eliminates distance restrictions for energy transfer between industrial microgrids. A case study illustrates the functionality of this topology, demonstrating optimized power transfer and decreased energy losses. This methodology allows industrial microgrids to enhance energy efficiency and productivity while minimizing operational costs.
Investigation and Evaluation of Microgrid Optimization TechniquesNevin Sawyer
The document summarizes an investigation into optimizing a microgrid consisting of distributed generators, solar panels, batteries, HVAC units, and loads using mixed integer linear programming and stochastic modeling. The objective was to minimize total costs by determining optimal power levels from each source at each time step under uncertainty. Constraints modeled technical limitations of the sources. Shadow price analysis evaluated the sensitivity of optimized solutions to demand changes and provided insights into the microgrid's economic competitiveness. Stochastic modeling increased accuracy but also complexity compared to a deterministic approach. The techniques were evaluated for practicality and effectiveness in utilizing microgrids.
Hourly Energy Sharing Model of Peer-to-Peer PV Prosumers for Microgrids with ...Plabon Saha
Local uses of photovoltaic (PV) energy within neighborhood PV prosumers become more economical than the individual operation of prosumers. In the present work, the hourly optimized total cost of energy sharing of peer-to-peer (P2P) PV prosumers for a microgrid is proposed. Initially, a dynamic internal pricing model is prepared for the energy sharing operation. Furthermore, considering the adjustable load of prosumers, an equiponderant cost model is formulated concerning economic costs and user interest. Finally, the formulated cost model is transformed into an optimization problem and is solved using the krill herd algorithm to get the ultimate optimized hourly total cost of energy sharing. This optimized cost provides the maximum economic profit to all the participating PV prosumers in the microgrid.
The document describes a proposed intelligent load management system with renewable energy integration for smart homes. Some key points:
- It presents an evolutionary algorithm-based demand side management model for scheduling household appliances optimally based on time-of-use pricing while integrating renewable energy.
- The model aims to optimize appliance operation times to minimize electricity costs, reduce peak demand on the grid, and make use of generated renewable energy from sources like solar.
- It categorizes home energy users into traditional, smart, and smart prosumers (who also generate renewable energy) and develops models for each. The proposed system uses algorithms like binary particle swarm optimization to generate optimized appliance schedules.
- Key components include an advanced meter
This document summarizes an article from the International Journal of Electrical Engineering and Technology that discusses modernizing traditional grids into smart grids through renewable energy sources. It provides background on the motivation to transition to smart grids, including addressing environmental concerns from fossil fuels and the inability of traditional grids to integrate renewable energy. The document outlines key features of smart grids, including reliability, flexibility, efficiency, sustainability, and enabling new energy markets. It also discusses challenges to smart grids, such as differences between energy generation and demand, transmitting power across grids, ensuring energy security, and developing standards to allow different technology components to work together.
This document summarizes and compares different energy management system optimization methods for DC microgrids. It first reviews related work that has analyzed EMS using techniques like genetic algorithms, particle swarm optimization, and other methods. It then presents mathematical models for key microgrid components like PV panels, batteries, and loads. Finally, it describes how the models are unified into an optimization problem and solved using the hybrid internal point method with genetic algorithms and particle swarm optimization to optimize energy flows and storage in the microgrid batteries. The results show these algorithms can intelligently manage energy to minimize battery charging/discharging and maximize storage life.
Renewable energy based dynamic tariff system for domestic load managementnooriasukmaningtyas
To deal with the present power-scenario, this paper proposes a model of an advanced energy management system, which tries to achieve peak clipping, peak to average ratio reduction and cost reduction based on effective utilization of distributed generations. This helps to manage conventional loads based on flexible tariff system. The main contribution of this work is the development of three-part dynamic tariff system on the basis of time of utilizing power, available renewable energy sources (RES) and consumers’ load profile. This incorporates consumers’ choice to suitably select for either consuming power from conventional energy sources and/or renewable energy sources during peak or off-peak hours. To validate the efficiency of the proposed model we have comparatively evaluated the model performance with existing optimization techniques using genetic algorithm and particle swarm optimization. A new optimization technique, hybrid greedy particle swarm optimization has been proposed which is based on the two aforementioned techniques. It is found that the proposed model is superior with the improved tariff scheme when subjected to load management and consumers’ financial benefit. This work leads to maintain a healthy relationship between the utility sectors and the consumers, thereby making the existing grid more reliable, robust, flexible yet cost effective.
An integrated framework_for_smart_microgrids_modeling_monitoring_control_comm...Premkumar K
The document proposes an integrated framework for modeling, monitoring, controlling, communicating, and verifying smart microgrids using service-oriented architectures. It discusses technical challenges in microgrid operation including dual grid-connected and islanding modes. The framework is intended to address issues like optimal generation scheduling, security assessment, demand management by enabling information exchange and integration with existing energy management systems. It aims to provide a platform, language, and vendor-independent solution.
The International Institute for Science, Technology and Education (IISTE) , International Journals Call for papaers: http://www.iiste.org/Journals
IRJET - Energy Management System on Operation of Smart GridIRJET Journal
This document discusses energy management systems for smart grids. It describes how energy management is important for maintaining balance between power supply and demand. Energy management can reduce costs and energy losses while increasing reliability. The document outlines different categories of customer load response based on response time and provides examples of equipment suited for each category. It also discusses feedback loops in smart grids and how they can create balancing or reinforcing effects.
Two-way Load Flow Analysis using Newton-Raphson and Neural Network MethodsIRJET Journal
The document presents a study comparing two-way load flow analysis using the Newton-Raphson method and a neural network method for networked microgrids. The optimal power flow problem is solved using both a conventional Newton-Raphson method and an artificial intelligence neural network method. Results show that the neural network method achieves minimum losses and higher efficiency compared to the Newton-Raphson method, with efficiencies of 99.3% and 97% respectively for the test networked microgrid system.
This paper proposes a novel distributed paradigm for energy scheduling in an islanded multi-agent microgrid utilizing a peer-to-peer management concept. The paradigm allows each agent to independently schedule local resources while participating in an hourly peer-to-peer energy market managed by the microgrid operator. A stochastic optimization approach addresses uncertainty from renewable energy sources using scenario-based modeling with copulas. Agents also use model predictive control and conditional value at risk to optimize operations over multiple time periods while managing prediction risk. The framework is tested on 10-bus and 33-bus microgrid systems to evaluate effectiveness and scalability.
Microgrid definition.
Microgrid components.
EPS challenges.
MG advantages and disadvantages.
Research scope.
The different microgrid benchmark models.
Microgrid Elements and Modeling.
Analysis and studies using the specified models.
Operation Modes of a Microgrid.
Designed system requirements.
Integrating Multiple Microgrids into an Active Network Management SystemSmarter Grid Solutions
This document summarizes a project between Southern Company and Smarter Grid Solutions to develop an active network management platform to integrate multiple microgrids. The project involves:
1) Defining use cases for interconnected, transition, and islanded microgrid operations and simulating them.
2) Deploying the active network management solution in a field trial at a test site to control distributed energy resources like solar, batteries and EVs across microgrids.
3) Implementing microgrid functionality in phases to allow multiple microgrids to operate autonomously yet coordinated.
A Novel Implementation of Demand Response on Smart Grid using Renewable Energ...IRJET Journal
The document summarizes a proposed control strategy for coordinating the operation of a photovoltaic (PV)/battery hybrid unit with other distributed generation units in an islanded microgrid. The control strategy allows the hybrid unit to:
1) Deliver maximum available PV power to the microgrid while charging the battery.
2) Absorb power from the microgrid to charge the battery without disrupting the power balance.
3) Match a varying load while storing surplus PV energy in the battery or curtailing PV power generation if needed.
Sliding Mode Adaptive Control of a Standalone Single Phase Microgrid Powered ...IRJET Journal
This document discusses an upgraded standalone single-phase microgrid system with an adaptive sliding mode control technique. The microgrid combines solar PV arrays, wind turbines, and battery energy storage. It can operate in both grid-connected and standalone modes. An adaptive sliding mode controller is designed and simulated to regulate the microgrid's power balance and voltage during changes in renewable generation and load. Simulation results show the controller effectively maintains power quality during steps in solar irradiation, wind speed, and load. The adaptive sliding mode control approach improves the microgrid's power efficiency and makes efficient use of renewable energy sources and battery storage.
ENERGY MANAGEMENT ALGORITHMS IN SMART GRIDS: STATE OF THE ART AND EMERGING TR...ijaia
The electric grid is radically evolving into the smart grid, which is characterized by improved energy
efficiency of available resources. The smart grid permits interactions among its computational and physical
elements thanks to the integration of Information and Communication Technologies (ICTs). ICTs provide
energy management algorithms and allow renewable energy integration and energy price minimization.
Given the importance of renewable energy, many researchers developed energy management (EM)
algorithms to minimize renewable energy intermittency. EM plays an important role in the control of users'
energy consumption and enables increased consumer participation in the market. These algorithms provide
consumers with information about their energy consumption patterns and help them adopt energy-efficient
behaviour. In this paper, we present a review of the state of the energy management algorithms. We define
a set of requirements for EM algorithms and evaluate them qualitatively. We also discuss emerging tools
and trends in this area.
Design and Control Issues of Microgrids : A SurveyIRJET Journal
This document summarizes key issues in the design and control of microgrids. It begins by defining microgrids and outlining their basic design considerations, which include suitable sizing and positioning of distributed energy resources. The document then discusses design aspects like optimal component selection and control strategies. It describes the hierarchical control approach for microgrids, with primary control focusing on voltage/frequency regulation, secondary on deviation mitigation, and tertiary on economic optimization. Finally, it outlines some major issues in microgrid design and control, specifically islanding detection challenges and non-detection zones, where changes in voltage and frequency may not trigger detection.
Interconnecting industrial multi-microgrids using bidirectional hybrid energy...IJECEIAES
Sharing and exchange energy among nearby industrial microgrids are crucial, especially with high energy requirements for their production targets and costly energy storage systems that may be oversized for their operations. Facilitating energy exchange can provide an economic advantage for industrial production by utilizing cheaper energy sources and reducing production costs. This manuscript presents an efficient approach for transferring large energy packets with minimal energy losses using
high-voltage direct current (HVDC) energy transmission. The manuscript methodology focuses on implementing an industrial multi-microgrid using a modular multilevel converter. This converter utilizes two power link channels: a three-phase AC and an HVDC link, creating a hybrid energy transmission between microgrids. When a substantial amount of energy to transfer, the HVDC method enhances overall efficiency by reducing copper losses and mitigating issues associated with the AC link, such as harmonics and skin effects. The modular multilevel converter topology offers high flexibility and the use of fewer converters. Additionally, the HVDC link eliminates distance restrictions for energy transfer between industrial microgrids. A case study illustrates the functionality of this topology, demonstrating optimized power transfer and decreased energy losses. This methodology allows industrial microgrids to enhance energy efficiency and productivity while minimizing operational costs.
Investigation and Evaluation of Microgrid Optimization TechniquesNevin Sawyer
The document summarizes an investigation into optimizing a microgrid consisting of distributed generators, solar panels, batteries, HVAC units, and loads using mixed integer linear programming and stochastic modeling. The objective was to minimize total costs by determining optimal power levels from each source at each time step under uncertainty. Constraints modeled technical limitations of the sources. Shadow price analysis evaluated the sensitivity of optimized solutions to demand changes and provided insights into the microgrid's economic competitiveness. Stochastic modeling increased accuracy but also complexity compared to a deterministic approach. The techniques were evaluated for practicality and effectiveness in utilizing microgrids.
Hourly Energy Sharing Model of Peer-to-Peer PV Prosumers for Microgrids with ...Plabon Saha
Local uses of photovoltaic (PV) energy within neighborhood PV prosumers become more economical than the individual operation of prosumers. In the present work, the hourly optimized total cost of energy sharing of peer-to-peer (P2P) PV prosumers for a microgrid is proposed. Initially, a dynamic internal pricing model is prepared for the energy sharing operation. Furthermore, considering the adjustable load of prosumers, an equiponderant cost model is formulated concerning economic costs and user interest. Finally, the formulated cost model is transformed into an optimization problem and is solved using the krill herd algorithm to get the ultimate optimized hourly total cost of energy sharing. This optimized cost provides the maximum economic profit to all the participating PV prosumers in the microgrid.
The document describes a proposed intelligent load management system with renewable energy integration for smart homes. Some key points:
- It presents an evolutionary algorithm-based demand side management model for scheduling household appliances optimally based on time-of-use pricing while integrating renewable energy.
- The model aims to optimize appliance operation times to minimize electricity costs, reduce peak demand on the grid, and make use of generated renewable energy from sources like solar.
- It categorizes home energy users into traditional, smart, and smart prosumers (who also generate renewable energy) and develops models for each. The proposed system uses algorithms like binary particle swarm optimization to generate optimized appliance schedules.
- Key components include an advanced meter
This document summarizes an article from the International Journal of Electrical Engineering and Technology that discusses modernizing traditional grids into smart grids through renewable energy sources. It provides background on the motivation to transition to smart grids, including addressing environmental concerns from fossil fuels and the inability of traditional grids to integrate renewable energy. The document outlines key features of smart grids, including reliability, flexibility, efficiency, sustainability, and enabling new energy markets. It also discusses challenges to smart grids, such as differences between energy generation and demand, transmitting power across grids, ensuring energy security, and developing standards to allow different technology components to work together.
This document summarizes and compares different energy management system optimization methods for DC microgrids. It first reviews related work that has analyzed EMS using techniques like genetic algorithms, particle swarm optimization, and other methods. It then presents mathematical models for key microgrid components like PV panels, batteries, and loads. Finally, it describes how the models are unified into an optimization problem and solved using the hybrid internal point method with genetic algorithms and particle swarm optimization to optimize energy flows and storage in the microgrid batteries. The results show these algorithms can intelligently manage energy to minimize battery charging/discharging and maximize storage life.
Renewable energy based dynamic tariff system for domestic load managementnooriasukmaningtyas
To deal with the present power-scenario, this paper proposes a model of an advanced energy management system, which tries to achieve peak clipping, peak to average ratio reduction and cost reduction based on effective utilization of distributed generations. This helps to manage conventional loads based on flexible tariff system. The main contribution of this work is the development of three-part dynamic tariff system on the basis of time of utilizing power, available renewable energy sources (RES) and consumers’ load profile. This incorporates consumers’ choice to suitably select for either consuming power from conventional energy sources and/or renewable energy sources during peak or off-peak hours. To validate the efficiency of the proposed model we have comparatively evaluated the model performance with existing optimization techniques using genetic algorithm and particle swarm optimization. A new optimization technique, hybrid greedy particle swarm optimization has been proposed which is based on the two aforementioned techniques. It is found that the proposed model is superior with the improved tariff scheme when subjected to load management and consumers’ financial benefit. This work leads to maintain a healthy relationship between the utility sectors and the consumers, thereby making the existing grid more reliable, robust, flexible yet cost effective.
An integrated framework_for_smart_microgrids_modeling_monitoring_control_comm...Premkumar K
The document proposes an integrated framework for modeling, monitoring, controlling, communicating, and verifying smart microgrids using service-oriented architectures. It discusses technical challenges in microgrid operation including dual grid-connected and islanding modes. The framework is intended to address issues like optimal generation scheduling, security assessment, demand management by enabling information exchange and integration with existing energy management systems. It aims to provide a platform, language, and vendor-independent solution.
The International Institute for Science, Technology and Education (IISTE) , International Journals Call for papaers: http://www.iiste.org/Journals
IRJET - Energy Management System on Operation of Smart GridIRJET Journal
This document discusses energy management systems for smart grids. It describes how energy management is important for maintaining balance between power supply and demand. Energy management can reduce costs and energy losses while increasing reliability. The document outlines different categories of customer load response based on response time and provides examples of equipment suited for each category. It also discusses feedback loops in smart grids and how they can create balancing or reinforcing effects.
Two-way Load Flow Analysis using Newton-Raphson and Neural Network MethodsIRJET Journal
The document presents a study comparing two-way load flow analysis using the Newton-Raphson method and a neural network method for networked microgrids. The optimal power flow problem is solved using both a conventional Newton-Raphson method and an artificial intelligence neural network method. Results show that the neural network method achieves minimum losses and higher efficiency compared to the Newton-Raphson method, with efficiencies of 99.3% and 97% respectively for the test networked microgrid system.
This paper proposes a novel distributed paradigm for energy scheduling in an islanded multi-agent microgrid utilizing a peer-to-peer management concept. The paradigm allows each agent to independently schedule local resources while participating in an hourly peer-to-peer energy market managed by the microgrid operator. A stochastic optimization approach addresses uncertainty from renewable energy sources using scenario-based modeling with copulas. Agents also use model predictive control and conditional value at risk to optimize operations over multiple time periods while managing prediction risk. The framework is tested on 10-bus and 33-bus microgrid systems to evaluate effectiveness and scalability.
Microgrid definition.
Microgrid components.
EPS challenges.
MG advantages and disadvantages.
Research scope.
The different microgrid benchmark models.
Microgrid Elements and Modeling.
Analysis and studies using the specified models.
Operation Modes of a Microgrid.
Designed system requirements.
Integrating Multiple Microgrids into an Active Network Management SystemSmarter Grid Solutions
This document summarizes a project between Southern Company and Smarter Grid Solutions to develop an active network management platform to integrate multiple microgrids. The project involves:
1) Defining use cases for interconnected, transition, and islanded microgrid operations and simulating them.
2) Deploying the active network management solution in a field trial at a test site to control distributed energy resources like solar, batteries and EVs across microgrids.
3) Implementing microgrid functionality in phases to allow multiple microgrids to operate autonomously yet coordinated.
A Novel Implementation of Demand Response on Smart Grid using Renewable Energ...IRJET Journal
The document summarizes a proposed control strategy for coordinating the operation of a photovoltaic (PV)/battery hybrid unit with other distributed generation units in an islanded microgrid. The control strategy allows the hybrid unit to:
1) Deliver maximum available PV power to the microgrid while charging the battery.
2) Absorb power from the microgrid to charge the battery without disrupting the power balance.
3) Match a varying load while storing surplus PV energy in the battery or curtailing PV power generation if needed.
Sliding Mode Adaptive Control of a Standalone Single Phase Microgrid Powered ...IRJET Journal
This document discusses an upgraded standalone single-phase microgrid system with an adaptive sliding mode control technique. The microgrid combines solar PV arrays, wind turbines, and battery energy storage. It can operate in both grid-connected and standalone modes. An adaptive sliding mode controller is designed and simulated to regulate the microgrid's power balance and voltage during changes in renewable generation and load. Simulation results show the controller effectively maintains power quality during steps in solar irradiation, wind speed, and load. The adaptive sliding mode control approach improves the microgrid's power efficiency and makes efficient use of renewable energy sources and battery storage.
ENERGY MANAGEMENT ALGORITHMS IN SMART GRIDS: STATE OF THE ART AND EMERGING TR...ijaia
The electric grid is radically evolving into the smart grid, which is characterized by improved energy
efficiency of available resources. The smart grid permits interactions among its computational and physical
elements thanks to the integration of Information and Communication Technologies (ICTs). ICTs provide
energy management algorithms and allow renewable energy integration and energy price minimization.
Given the importance of renewable energy, many researchers developed energy management (EM)
algorithms to minimize renewable energy intermittency. EM plays an important role in the control of users'
energy consumption and enables increased consumer participation in the market. These algorithms provide
consumers with information about their energy consumption patterns and help them adopt energy-efficient
behaviour. In this paper, we present a review of the state of the energy management algorithms. We define
a set of requirements for EM algorithms and evaluate them qualitatively. We also discuss emerging tools
and trends in this area.
This project report explores the critical domain of cybersecurity, focusing on the practices and principles of ethical hacking as a proactive defense mechanism. With the rapid growth of digital technologies, organizations face a wide range of threats including data breaches, malware attacks, phishing scams, and ransomware. Ethical hacking, also known as penetration testing, involves simulating cyberattacks in a controlled and legal environment to identify system vulnerabilities before malicious hackers can exploit them.
International Journal of Advance Robotics & Expert Systems (JARES)jaresjournal868
Advance Robotics & Expert Systems carry original articles, review articles, case studies and short communications from all over the world. The main aim of this journal is to extend the state of the art on theoretical, computational and experimental aspects of expert systems related to the applied fields such as transportation, surveillance, medical and industrial domains. This journal is also concentrated on kinematics, dynamics and syntheses of various robot locomotion mechanisms such as walk, jump, run, slide, skate, swim, fly, roll etc.
Test your knowledge of the Python programming language with this quiz! Covering topics such as:
- Syntax and basics
- Data structures (lists, tuples, dictionaries, etc.)
- Control structures (if-else, loops, etc.)
- Functions and modules
- Object-Oriented Programming (OOP) concepts
Challenge yourself and see how well you can score!
A passionate and result-oriented with over 28 years of multi-disciplinary experience in engineering, construction & maintenance management, and quality control works in oil and gas (offshore and onshore), industrial, and commercial projects. With proven ability in supervising design engineering (FEED) and managing construction, testing, commissioning, and handover of various scales of mechanical, electrical, plumbing, fire protection (MEPF), plant mechanical equipment (static/ rotating), piping, pipeline, and civil projects. A licensed Mechanical Engineer, Registered Master Plumber (Plumbing Engineer equivalent), Certified Project Management Professional (PMP), Occupational Health & Safety Management NEBOSH International General Certificate (IG1) passer, ISO QMS Auditor, ISO QMS, ISO EMS, ISO IMS Implementor, and Master in Business Administration (MBA).
Although the exploitation of GWO advances sharply, it has limitations for continuous implementing exploration. On the other hand, the EHO algorithm easily has shown its capability to prevent local optima. For hybridization and by considering the advantages of GWO and the abilities of EHO, it would be impressive to combine these two algorithms. In this respect, the exploitation and exploration performances and the convergence speed of the GWO algorithm are improved by combining it with the EHO algorithm. Therefore, this paper proposes a new hybrid Grey Wolf Optimizer (GWO) combined with Elephant Herding Optimization (EHO) algorithm. Twenty-three benchmark mathematical optimization challenges and six constrained engineering challenges are used to validate the performance of the suggested GWOEHO compared to both the original GWO and EHO algorithms and some other well-known optimization algorithms. Wilcoxon's rank-sum test outcomes revealed that GWOEHO outperforms others in most function minimization. The results also proved that the convergence speed of GWOEHO is faster than the original algorithms.
Welcome to MIND UP: a special presentation for Cloudvirga, a Stewart Title company. In this session, we’ll explore how you can “mind up” and unlock your potential by using generative AI chatbot tools at work.
Curious about the rise of AI chatbots? Unsure how to use them-or how to use them safely and effectively in your workplace? You’re not alone. This presentation will walk you through the practical benefits of generative AI chatbots, highlight best practices for safe and responsible use, and show how these tools can help boost your productivity, streamline tasks, and enhance your workday.
Whether you’re new to AI or looking to take your skills to the next level, you’ll find actionable insights to help you and your team make the most of these powerful tools-while keeping security, compliance, and employee well-being front and center.
In the 1993 AASHTO flexible pavement design equation, the structural number (SN) cannot be calculated explicitly based on other input parameters. Therefore, in order to calculate the SN, it is necessary to approximate the relationship using the iterative approach or using the design chart. The use of design chart reduces the accuracy of calculations and, on the other hand, the iterative approach is not suitable for manual calculations. In this research, an explicit equation has been developed to calculate the SN in the 1993 AASHTO flexible pavement structural design guide based on response surface methodology (RSM). RSM is a collection of statistical and mathematical methods for building empirical models. Developed equation based on RMS makes it possible to calculate the SN of different flexible pavement layers accurately. The coefficient of determination of the equation proposed in this study for training and testing sets is 0.999 and error of this method for calculating the SN in most cases is less than 5%. In this study, sensitivity analysis was performed to determine the degree of importance of each independent parameter and parametric analysis was performed to determine the effect of each independent parameter on the SN. Sensitivity analysis shows that the log(W8.2) has the highest degree of importance and the ZR parameter has the lowest one.
Department of Environment (DOE) Mix Design with Fly Ash.MdManikurRahman
Concrete Mix Design with Fly Ash by DOE Method. The Department of Environmental (DOE) approach to fly ash-based concrete mix design is covered in this study.
The Department of Environment (DOE) method of mix design is a British method originally developed in the UK in the 1970s. It is widely used for concrete mix design, including mixes that incorporate supplementary cementitious materials (SCMs) such as fly ash.
When using fly ash in concrete, the DOE method can be adapted to account for its properties and effects on workability, strength, and durability. Here's a step-by-step overview of how the DOE method is applied with fly ash.