Smart DC Microgrid

2022 ◽  
pp. 672-699
Author(s):  
Brijendra Pratap Singh ◽  
M M Gore
Keyword(s):  
Demand Response ◽  
Physical System ◽  
Cyber Physical System ◽  
Physical Processes ◽  
Control Logic ◽  
Dc Microgrid ◽  
Point Tracking ◽  
Demand Response Program ◽  
Power Point ◽  
The Evolution Of Industry

The objective of this chapter is to elucidate on microgrid technologies, a comparison of direct current (DC) microgrid technology and alternating current (AC) microgrid technology, the role of the information and communication technology, demand response programs, and the evolution of Industry 4.0 in detail. The microgrid is a cyber-physical system. ICT is used for computing control algorithms and sending control information to actuators for physical processes. In a cyber-physical system, the physical processes, which are governed by the laws of physics, are controlled by computers. The computers are used for computing or executing the algorithms (i.e., the control logic) and the result is sent to the actuators in the form of control signal for actual control. In a microgrid, a consumer can act as a producer also, which is termed as the prosumer. This chapter explains the maximum power point tracking algorithm, software-defined battery, the operation of parallel converters, the working of prosumer, the demand response program, communication technologies, and the (industrial) Internet of Things.

Smart DC Microgrid

2019 ◽  
pp. 100-128 ◽  
Author(s):  
Brijendra Pratap Singh ◽  
M M Gore
Keyword(s):  
Demand Response ◽  
Physical System ◽  
Cyber Physical System ◽  
Physical Processes ◽  
Control Logic ◽  
Dc Microgrid ◽  
Point Tracking ◽  
Demand Response Program ◽  
Power Point ◽  
The Evolution Of Industry

The objective of this chapter is to elucidate on microgrid technologies, a comparison of direct current (DC) microgrid technology and alternating current (AC) microgrid technology, the role of the information and communication technology, demand response programs, and the evolution of Industry 4.0 in detail. The microgrid is a cyber-physical system. ICT is used for computing control algorithms and sending control information to actuators for physical processes. In a cyber-physical system, the physical processes, which are governed by the laws of physics, are controlled by computers. The computers are used for computing or executing the algorithms (i.e., the control logic) and the result is sent to the actuators in the form of control signal for actual control. In a microgrid, a consumer can act as a producer also, which is termed as the prosumer. This chapter explains the maximum power point tracking algorithm, software-defined battery, the operation of parallel converters, the working of prosumer, the demand response program, communication technologies, and the (industrial) Internet of Things.

scholarly journals A maximum power point tracking technique using modified hill climbing (MHC) method in DC microgrid application

2020 ◽  
Author(s):  
Zaenal Efendi ◽  
Epyk Sunarno ◽  
Farid Dwi Murdianto ◽  
Rachma Prilian Eviningsih ◽  
Lucky Pradigta Setiya Raharja ◽  
...  
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Hill Climbing ◽  
Maximum Power Point ◽  
Dc Microgrid ◽  
Tracking Technique ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

scholarly journals Experimental Implementation of a Flexible PV Power Control Mechanism in a DC Microgrid

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1233 ◽  
Author(s):  
Hongwei Wu ◽  
Fabrice Locment ◽  
Manuela Sechilariu
Keyword(s):  
Control Mechanism ◽  
Research Work ◽  
Dc Microgrid ◽  
Physical Constraints ◽  
Point Tracking ◽  
Pv Panel ◽  
Experimental Implementation ◽  
Variable Nature ◽  
Power Point ◽  
Pv Generation

The intermittent and highly variable nature of photovoltaic (PV) sources is always the major obstacle to the growth of their deployment. Research work is increasingly demonstrating that PV generation should not only be maximized but also flexible based on the system requirements. This article presents a simple and flexible PV control mechanism, which can seamlessly switch between maximum power point tracking mode and power limiting mode. It can be integrated into a DC microgrid for efficient energy management. The proposed mechanism has two configurations that respectively converge to a lower and a higher PV panel voltage to perform PV shedding. The experimental validation carried out in this study shows that this control can effectively adjust the PV generation despite some physical constraints. The limitations of the control mechanism and the energy efficiency are also analyzed. It can be concluded that each configuration can be particularly useful depending on the different application scenarios.

Maximum Power Point Tracking and Voltage Control in a Solar-PV based DC Microgrid Using Simulink

2021 ◽  
Author(s):  
Frank Miyagishima ◽  
Sijo Augustine ◽  
Olga Lavrova ◽  
Hamed Nademi ◽  
Satish Ranade ◽  
...  
Keyword(s):  
Maximum Power Point Tracking ◽  
Voltage Control ◽  
Maximum Power ◽  
Solar Pv ◽  
Maximum Power Point ◽  
Dc Microgrid ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Energy trading and control of islanded DC microgrid using multi-agent systems

2021 ◽  
Vol 17 (2) ◽  
pp. 113-128
Author(s):  
Diana Rwegasira ◽  
Imed Ben Dhaou ◽  
Masoumeh Ebrahimi ◽  
Anders Hallén ◽  
Nerey Mvungi ◽  
...  
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Dynamic Pricing ◽  
Energy Sector ◽  
Load Shedding ◽  
Dc Microgrid ◽  
Energy Trading ◽  
Development Framework ◽  
Demand Response Program ◽  
Multi Agent

The energy sector is experiencing a revolution that is fuelled by a multitude of factors. Among them are the aging grid system, the need for cleaner energy and the increasing demands on energy sector. The demand-response program is an advanced feature in smart grid that strives to match suppliers to their demands using price-based and incentive programs. The objective of the work is to analyse the performance of the load shedding technique using dynamic pricing algorithm. The system was designed using multi-agent system (MAS) for a DC microgrid capable of real-time monitoring and controlling of power using price-based demand-response program. As a proof of concept, the system was implemented using intelligent physical agents, Java Agent Development Framework (JADE), and agent simulation platform (REPAST) with two residential houses (non-critical loads) and one hospital (critical load). The architecture has been implemented using embedded devices, relays, and sensors to control the operations of load shedding and energy trading in residential areas that have no access to electricity. The measured results show that the system can shed the load with the latency of less than 600 ms, and energy cost saving with an individual houses by 80% of the total cost with 2USD per day. The outcome of the studies demonstrates the effectiveness of the proposed multi-agent approach for real-time operation of a microgrid and the implementation of demand-response program.

scholarly journals DC-Microgrid System Design, Control, and Analysis

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 124 ◽  
Author(s):  
Adel El-Shahat ◽  
Sharaf Sumaiya
Keyword(s):  
Power Systems ◽  
Direct Current ◽  
Complete System ◽  
Systems Design ◽  
Maximum Power ◽  
Solar Pv ◽  
Pv System ◽  
Dc Microgrid ◽  
Point Tracking ◽  
Power Point

Recently direct current (DC) microgrids have drawn more consideration because of the expanding use of direct current (DC) energy sources, energy storages, and loads in power systems. Design and analysis of a standalone solar photovoltaic (PV) system with DC microgrid has been proposed to supply power for both DC and alternating current (AC) loads. The proposed system comprises of a solar PV system with boost DC/DC converter, Incremental conductance (IncCond) maximum power point tracking (MPPT), bi-directional DC/DC converter (BDC), DC-AC inverter and batteries. The proposed bi-directional DC/DC converter (BDC) lessens the component losses and upsurges the efficiency of the complete system after many trials for its components’ selection. Additionally, the IncCond MPPT is replaced by Perturb & Observe (P&O) MPPT, and a particle swarm optimization (PSO) one. The three proposed techniques’ comparison shows the ranking of the best choice in terms of the achieved maximum power and fast—dynamic response. Furthermore, a stability analysis of the DC microgrid system is investigated with a boost converter and a bidirectional DC-DC converter with the Lyapunov function for the system has been proposed. The complete system is designed and executed in a MATLAB/SIMULINK environment and validated utilizing an OPAL real-time simulator.

scholarly journals Industry 4.0 for the Construction Industry—How Ready Is the Industry?

2019 ◽  
Vol 9 (14) ◽  
pp. 2819 ◽  
Author(s):  
Raihan Maskuriy ◽  
Ali Selamat ◽  
Kherun Nita Ali ◽  
Petra Maresova ◽  
Ondrej Krejcar
Keyword(s):  
Construction Industry ◽  
Physical System ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Web Of Science ◽  
Spillover Effect ◽  
Cyber Physical System ◽  
Building Information Modelling ◽  
Building Information ◽  
The Evolution Of Industry

Technology and innovations have fueled the evolution of Industry 4.0, the fourth industrial revolution. Industry 4.0 encourages growth and development through its efficiency capacity, as documented in the literature. The growth of the construction industry is a subset of the universal set of the gross domestic product value; thus, Industry 4.0 has a spillover effect on the engineering and construction industry. In this study, we aimed to map the state of Industry 4.0 in the construction industry, to identify its key areas, and evaluate and interpret the available evidence. We focused our literature search on Web of Science and Scopus between January 2015 and May 2019. The search was dependent on the following keywords: “Industry 4.0” OR “Industrial revolution 4.0” AND TOPIC: “construction” OR “building”. From the 82 papers found, 20 full-length papers were included in this review. Results from the targeted papers were split into three clusters: technology, security, and management. With building information modelling (BIM) as the core in the cyber-physical system, the cyber-planning-physical system is able to accommodate BIM functionalities to improve construction lifecycle. This collaboration and autonomous synchronization system are able to automate the design and construction processes, and improve the ability of handling substantial amounts of heterogeneity-laden data. Industry 4.0 is expected to augment both the quality and productivity of construction and attract domestic and foreign investors.

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