scholarly journals Solar Powered Dc Nano-Grid with Multi Agent Control Strategy

2019 ◽  
Vol 9 (2S2) ◽  
pp. 971-977
Keyword(s):  
Renewable Energy Sources ◽  
Residential Building ◽  
Smart Homes ◽  
Agent Based ◽  
Comfort Levels ◽  
Central Controller ◽  
Flexible Loads ◽  
Multi Agent ◽  
Solar Powered ◽  
And Storage

Smart homes are typical examples of DC Nano-grids wherein multi-agent strategy is required for coordinating different entities to harness flexible load and storage to maximize the integration of intermittent renewable generation. This paper proposes a novel multi-agent approach for DC Nano-grids in smart homes with an aim to simultaneously maximize comfort levels and renewable integration. In the proposed approach, there are three agents: flexible loads, batteries, and renewable energy sources which interact among them for meeting the control objectives. The agents are coordinated using a centralized controller and based on its decision the flexibility is harnessed to the grid. The novelty of the approach is that the different agents communicate only to the central controller and not among themselves which reduces the communication among them. The advantage of the proposed approach is their ability to handle DC Nano-grids and using an agent-based approach within a residential building. The proposed multi-agent approach is illustrated on a lab-level DC Nano-grids pilot developed by the authors. Our results show that achieves maximum overall energy efficiency and minimum electricity bill and smooth control of various modes of operation.

scholarly journals An Innovative Stochastic Multi-Agent-Based Energy Management Approach for Microgrids Considering Uncertainties

Inventions ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 37 ◽  
Author(s):  
Sajad Ghorbani ◽  
Rainer Unland ◽  
Hassan Shokouhandeh ◽  
Ryszard Kowalczyk
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Energy Demand ◽  
Search Algorithm ◽  
Renewable Energy Sources ◽  
Management Approach ◽  
Agent Based ◽  
Multi Agent ◽  
Power Outputs ◽  
Microgrid Energy Management

In microgrids a major share of the energy production comes from renewable energy sources such as photovoltaic panels or wind turbines. The intermittent nature of these types of producers along with the fluctuation in energy demand can destabilize the grid if not dealt with properly. This paper presents a multi-agent-based energy management approach for a non-isolated microgrid with solar and wind units and in the presence of demand response, considering uncertainty in generation and load. More specifically, a modified version of the lightning search algorithm, along with the weighted objective function of the current microgrid cost, based on different scenarios for the energy management of the microgrid, is proposed. The probability density functions of the solar and wind power outputs, as well as the demand of the households, have been used to determine the amount of uncertainty and to plan various scenarios. We also used a particle swarm optimization algorithm for the microgrid energy management and compared the optimization results obtained from the two algorithms. The simulation results show that uncertainty in the microgrid normally has a significant effect on the outcomes, and failure to consider it would lead to inaccurate management methods. Moreover, the results confirm the excellent performance of the proposed approach.

scholarly journals Intelligent Optimization And Management System For Renewable Energy Systems Using Multi-Agent

2019 ◽  
Vol 8 (4) ◽  
pp. 352 ◽  
Author(s):  
Chahinaze Ameur ◽  
Sanaa Faquir ◽  
Ali Yahyaouy
Keyword(s):  
Renewable Energy ◽  
Wind Turbine ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Development Environment ◽  
Hybrid Energy ◽  
Load Demand ◽  
Multi Agent ◽  
And Storage ◽  
Storage Units

<p>Hybrid energy systems(HES) using renewable energy sources are an interesting solution for power stand-alone systems. However, the energy management of such systems is very complex. This paper presents a Multi Agent System(MAS) framework applied to manage the flow of energy in a hybrid stand-alone system. The proposed system consists of photovoltaic panels and a wind turbine along with batteries as storage units. The proposed MAS architecture composed of different agents(photovoltaic agent, wind turbine agent, supervisor agent, load controller agent, and storage agent) was developed to manage the flow of energy between the energy resources and the storage units for an isolated house. The agent-approach for HES is explained and the proposed MAS is presented and a simulation model is developed in the java agent development environment(JADE). The system was tested with empty batteries and full batteries and results showed that the system could satisfy the load demand while maintaining the level of the batteries between 30%(minimum discharging rate) and 80%(maximum charging rate).</p>

scholarly journals Qualitative Analysis of Intelligent Use of Demand and Generation in Microgrid

2020 ◽  
Vol 1 (1) ◽  
pp. 21-38
Author(s):  
Izhar Salam ◽  
Moatasim Billah ◽  
Muhammad Maaz
Keyword(s):  
Critical Load ◽  
Hardware Implementation ◽  
Renewable Energy Sources ◽  
Unit Cost ◽  
Emergency Situation ◽  
Load Management ◽  
End User ◽  
Power Sources ◽  
Central Controller ◽  
Multi Agent

There are reliable solutions for overcoming the mismanagements and inefficiencies in the microgrid, which have been discussed, in the following proposed study. It focuses on the utilization of Renewable Energy Sources (RES) for operating the microgrid in a smart way such that the supply demand ratio is balanced profiting both the utility user and the end user. Power sources are scheduled as per requirement based on their availability and per unit cost. Centralized Multi Agent System (MAS) technique is adopted in which a central controller controls the operation of the whole microgrid system. Load agents attached to the system are of two types, i.e., critical load and non-critical load. The power to the critical load is to be maintained as a result of which in case of any emergency situation the power supplied to the non-critical load is shed off in order to make the critical load running. Different techniques are utilized for load management. Demand Side Management (DSM) is one of those techniques in which the load shifts from peak to off-peak hours and vice versa. Further, on the simulation of the proposed study has been performed in MATLAB/Simulink software and its hardware implementation has been done as well. The output results achieved indicates the supply to the load agents depending upon the availability of the power sources.

Evolutionary Design of Cellular Self-Organizing Systems

2013 ◽  
Author(s):  
James Humann ◽  
Yan Jin
Keyword(s):  
Fitness Function ◽  
Emergent Behavior ◽  
Local Interaction ◽  
System Level ◽  
Self Organization ◽  
Agent Based ◽  
Simple Set ◽  
Central Controller ◽  
Multi Agent ◽  
Self Organizing

In this paper, a genetic algorithm (GA) is used to discover interaction rules for a cellular self-organizing (CSO) system. The CSO system is a group of autonomous, independent agents that perform tasks through self-organization without any central controller. The agents have a local neighborhood of sensing and react only to other agents within this neighborhood. Their interaction rules are a simple set of direction vectors based on a flocking model. The five local interaction rules are assigned relative weights, and the agents self-organize to display some emergent behavior at the system level. The engineering challenge is to identify which sets of local rules will cause certain desired global behaviors. The global required behaviors of the system, such as flocking or exploration, are translated into a fitness function that can be evaluated at the end of a multi-agent based simulation run. The GA works by tuning the relative weights of the local interaction rules so that the desired global behavior emerges, judged by the fitness function. The GA approach is shown to be successful in tuning the weights of these interaction rules on simulated CSO systems, and, in some cases, the GA actually evolved qualitatively different local interaction “strategies” that displayed equivalent emergent capabilities.

A Multi-agent based Micro Grid Operation Method

2013 ◽  
Vol 133 (9) ◽  
pp. 1652-1657 ◽  
Author(s):  
Takeshi Nagata ◽  
Kosuke Kato ◽  
Masahiro Utatani ◽  
Yuji Ueda ◽  
Kazuya Okamoto ◽  
...  
Keyword(s):  
Agent Based ◽  
Operation Method ◽  
Multi Agent ◽  
Micro Grid ◽  
Grid Operation

Browser Security Attacks and Detection Techniques: A Case of Tabnabbing

2020 ◽  
Vol 8 (1) ◽  
pp. 33-41
Author(s):  
Dr. S. Sarika ◽  
Keyword(s):  
Credit Card ◽  
State Of The Art ◽  
Experimental Results ◽  
Detection Technique ◽  
Security Attacks ◽  
Agent Based ◽  
Detection Techniques ◽  
Browser Security ◽  
Cyber Threats ◽  
Multi Agent

Phishing is a malicious and deliberate act of sending counterfeit messages or mimicking a webpage. The goal is either to steal sensitive credentials like login information and credit card details or to install malware on a victim’s machine. Browser-based cyber threats have become one of the biggest concerns in networked architectures. The most prolific form of browser attack is tabnabbing which happens in inactive browser tabs. In a tabnabbing attack, a fake page disguises itself as a genuine page to steal data. This paper presents a multi agent based tabnabbing detection technique. The method detects heuristic changes in a webpage when a tabnabbing attack happens and give a warning to the user. Experimental results show that the method performs better when compared with state of the art tabnabbing detection techniques.

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