Agent Development Environment Research Articles

Application of multi agent systems for advanced energy management in cyber physical hybrid microgrid systems

This paper develops a multi agent system in real time for hybrid microgrids as advanced energy management (ADEM) protocol using a Java agent development environment (JADE) frame work. The proposed system is configured with two micro-grids, each having 1kw solar photo voltaic power, 1.5Kw wind power, 24 V, 150AH battery along with a local load, thus making it a hybrid Microgrid, modelled in MATLAB/Simulink. Due stability constraints while using MATLAB/Simulink, in a multi-threading environment, a middle ware called Multi agent Control Using Simulink with Jade Extension (MACSimJX) is adopted. The microgrid environment variables are captured through sensors, delivered to the agents operations in JADE, for the implementation of dynamic operation in hybrid microgrids. This results in maximizing operational efficiency of hybrid microgrids system. The simulation suggests that MAS can successfully manage dynamic loads, generated power in real time microgrids.

A Proposed Architecture for Local-Host and AWS with Multiagent System

Cloud computing has become one of the leading technologies in the world today. The benefits of cloud computing affect end users directly. There are several cloud computing frameworks, and each has ways of monitoring and providing resources. Cloud computing eliminates customer requirements such as expensive system configuration and massive infrastructure while improving dependability and scalability. From the user’s perspective, cloud computing makes it easy to upload multiagents and operate on different web services. In this paper, the authors used a restful web service and an agent system to discuss, deployments, and analysis of load performance parameters like memory use, central processing unit (CPU) utilization, network latency, etc., both on localhost and an Amazon Web Service Elastic Cloud Computing (AWS-EC2) server. The Java Agent Development Environment (JADE) tool has been used to propose an architecture and conduct a comparative study on both local and remote servers. JADE is an open-source tool for maintaining applications on AWS infrastructure. The focus of the study should be to reduce the complexity and time of load performance parameters by using an agent system on a cloud server instead of establishing a massive infrastructure on a local system, even for a small application.

Advanced energy management and frequency control of distributed microgrid using multi-agent systems

AbstractOne of the main objectives of the Energy Management System (EMS) is to achieve a very high level of flexibility, stability, and the system must be able to adapt to most changes in the distribution network. This paper proposes a multi-agent system-based microgrid energy management to balance the energy supply and demand by feasibly integrating the energy storage system and demand response. An overall power management strategy is necessary to manage power flows among all interconnected elements of the microgrid. The principal contribution of this paper is an energy management system based on intelligent agents; each agent uses the microgrid data to manage the power flow in the microgrid. The interaction between agents proposed is simulated using JADE (Java Agent Development Environment) and the microgrid model is simulated using MATLAB/Simulink, both platforms are connected through the MACSimJX middleware for a dynamic simulation.

Isolated Microgrid Management Using a Multi-Agent System

Solar energy offers a considerable potential for the energy market and it brings many challenges for the actual research. In order to meet the economic and the environmental expectation, the management of an isolated microgrid needs to be more efficient and profitable. In this paper a Multi-Agent System (MAS) is proposed in order to manage an isolated photovoltaic microgrid. The proposed approach presented in this paper improves the management of an isolated decentralized microgrid. It takes in account load voltage constraints, ensures the power demand, reduces chattering phenomenon on the storage system, and it maintains the photovoltaic panel operating in its maximum efficiency point. Finally, the proposed method is evaluated throw three scenarios, and the results are obtained by simulation using MATLAB/Simulink and JADE (Java Agent Development Environment).

Fault diagnosis, service restoration, and data loss mitigation through multi-agent system in a smart power distribution grid

ABSTRACT Smart power distribution grid is equipped with different sensors and smart meters for getting measurements at different nodes. Additionally, for monitoring and control purpose Intelligent Electronic Devices (IEDs) are also installed. On the occurrence of fault in the grid, power utility implement a Fault Detection, Isolation and Restoration (FDIR) scheme to restore the power in healthy section of the network, this process is known as Service Restoration (SR). In the existing scenario, a centralized control scheme is used for monitoring and control of distribution grid. This control scheme is slow in terms of deployment of FDIR plan. So, the authors propose a multi-agent-based de-centralized control scheme for FDIR. For this multi-agent system, different agents are defined to perform tasks of fault detection, fault isolation, and restoration. Also, the aspect of communication among agents is presented and to tackle data loss problem, a Compressive Sensing (CS) based technique is applied. A novel Support Vector Machine (SVM) approach is proposed for fault classification. For SR, a Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) based method is used and is validated through its application for different fault scenarios in an IEEE 69 bus test system. Also, for testing of data loss mitigation agent, a real-time Phasor Measurement Unit (PMU) data is taken. The whole framework is designed in a python-based Smart Python Agent Development Environment (SPADE) and the related computation is done using MATLAB.

Holonic agent-based approach for system-level remaining useful life estimation with stochastic dependence

ABSTRACT The emerging behavior in complex systems is more complicated than the sum of the behaviors of their constituent parts. This behavior involves the propagation of faults between the parts and requires information about how the parts are related. Therefore, the prognostic function at the system-level becomes a very tough task. Conventional approaches focus on identifying faults and their probabilities of occurrence. In complex systems, this can create statistical limitations for prognostic function where component fault relies on the connected components in the system and their state of degradations. In this paper, a new Holonic agent-based approach is proposed for system-level remaining useful life (S-RUL) estimation with different dependencies. As the proposed approach can capture fault/failure mode propagation and interactions that occur in the system all the way up through the component and eventually system level, it can work as an automatic testing-tool in reliability tasks. Through a numerical example, the implementation is done in Java Agent Development Environment with and without consideration of stochastic dependence. Results show that the indirect effect of influencing components has a massive impact on the S-RUL, and the impact of stochastic dependencies should not be ignored, especially in the early stages of the system design.

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

<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>

A Distributed Electricity Trading System in Active Distribution Networks Based on Multi-Agent Coalition and Blockchain

The prevalence of distributed energy resources encourages the concept of an electricity “Prosumer (Producer and Consumer)”. This paper proposes a distributed electricity trading system to facilitate the peer-to-peer electricity sharing among prosumers. The proposed system includes two layers. In the first layer, a multi-agent system is designed to support the prosumer network, and an agent coalition mechanism is proposed to enable the prosumers to form coalitions and negotiate electricity trading. In the second layer, a Blockchain based transaction settlement mechanism is proposed to enable the trusted and secure settlement of electricity trading transactions formed in the first layer. Simulations are conducted based on the java agent development environment to validate the proposed electricity trading process.

Simulation tools for a smart grid and energy management for microgrid with wind power using multi-agent system

The smart grid concept is predicated upon the pervasive use of advanced digital communication, information techniques, and artificial intelligence for the current power system to be more characteristics on the real-time monitoring and controlling of the supply/demand. Therefore, in recent years, researchers increasingly couple distinct simulators to form novel “co-simulations.” In this article, we will present a survey of different electrical power and communication simulators, a literature survey of 20 smart grid co-simulations frameworks, and the characteristics of each platform applicable in the intelligent electrical network. Finally, we proposed multi-agent systems for controlling the microgrid that consists of wind power and storage system using MACSimJX co-simulation that combines Simulink simulator and JADE (Java Agent Development Environment).

Knowledge and agent-based system for decentralised scheduling in manufacturing

The aim of the research paper is to develop algorithms for manufacturers’ agents that would allow them to sequence their own operation plans and to develop a multi-agent infrastructure to allow operation pair agents to cooperatively adjust the timing of manufacturing operations. The scheduling problem consisted of jobs with fixed process plans and of manufacturers collectively offering the necessary operations for the jobs. Manufacturer agents sequenced and pair agents timed each operation as and when required. Timing an operation triggered a cascade of conflicts along the job process plan that other pair agents would pick up on and would take action accordingly. The conventional approach performs conflict resolution in series and manufacturer agents as well as pair agents wait until they are allowed to sequence and time the next operation. The limiting assumption behind that approach was systematically removed, and the proposed approach allowed manufacturers to perform operation scheduling in parallel, cutting down tenfold on the computation time. The multi-agent infrastructure consists of the Protege knowledge base, the Pellet semantic reasoner and the Workflows and Agent Development Environment (WADE). The case studies used were the MT6, MT10 and LA19 job shop scheduling problems; and an industrial use case was provided to give context to the manufacturing environment investigated. Although there were benefits from the decentralised manufacturing system, we noted an optimality loss of 34% on the makespans. However, for scalability, our approach showed good promise.

Multi-Agent Based Diagnostic Model for Breast Tumour Classification

Breast cancer is one of the most hazardous of all types of cancer affecting mainly women. It is the second leading cause of death in Nigerian women. It is difficult to classify breast tumour. The diagnosis of breast cancer on patients in hospitals and clinics is highly subjective and it is reliant on the physician’s expertise. This may often lead to incorrect diagnosis and long waiting time to diagnose breast tumour which may increase the possibility of Cancer metastasizing. This study focused on developing a multi-agent based model for diagnosis of breast tumours using the k-Nearest Neighbor (k-NN) algorithm by classifying the nature of the tumours based on their associated patterns of symptoms and other risk factors of Cancer diseases. A k-NN algorithm using Java and MYSQ was developed to extract and classify the symptoms associated with Breast Cancer. Java Agent Development Environment (JADE) was used for the modeling and simulation. The accuracy score was tested on a breast tumour clinical datasets which were gotten and formed from Federal Medical Centers (FMC) Yola and Gombe in Nigeria. The experimental result of the prediction model shows a percentage accuracy score of 98.9%.

Multi-Agent-Based Performance Analysis of Classifiers for Breast Tumours

The challenging effect of selecting the best classifier among many classifier algorithms has been a big problem in data mining. Machine learning is widely used in bioinformatics and particularly in breast cancer diagnosis. This study is based on developing and evaluating different classifier algorithm (k-NN, J48, Decision table, Decision stump, and Naive Bayes) in order to find the best among them using multi-agent platform and MYSQL for the diagnosis of breast tumors based on associated symptoms and risk factors of cancer diseases. Java Agent Development Environment (JADE) was used for the modeling and simulation. The results and the accuracy score were tested with a breast tumor clinical datasets which were gotten and formed from FMC Yola and FMC Gombe in Nigeria using 10- fold Cross-validation method. The results of the analysis reveal that k-NN classifier has a greater performance capability over other classification algorithms; hence, it is selected to be the best among the tested classifiers with higher accuracy score and lower false positive rate value.

Agent-Based Regression Test Case Generation using Class Diagram, Use cases and Activity Diagram

In Regression testing, test case generation is a process of generating test cases from the existing test suite to ensure that modifications made in the system have not affected its existing functionality. The use of modeling based UML class diagram identifies changes at syntax level, whereas use cases and activity diagram identify changes at semantic level. In this research, we have used the combination of UML class diagram, use cases and activity diagram to identify changes at both syntax and semantics level. We compared UML class diagrams, use cases and activity diagrams of old and modified code to identify these changes. It is found that the use of UML class diagram, use cases and activity diagram results in better identification of changes and hence leads to efficient test case generation. Additionally, agents developed in Java Agent Development Environment are used to collect these changes from different stake holders in the distributed environment. The distribution of testing tasks among mobile agents reduces the average time required for generation of test cases in regression testing.

Micro-grid Grid Outage Management using Multi Agent Systems

The aim of this paper is to evolve a Multi Agent System (MAS) for grid outage management in energy administration of a micro-grid. We consider a micro-grid consisting of two systems each containing a solar Photo Voltaic (PV) system, wind system, a local consumer, and a battery. Initially we observe and record the load patterns and solar and wind power generated in the two units. Following which we implement outage management using Multi Agent System of the micro-grid with smart grid frame work. Simulation of the model is developed in Java Agent Development Environment (JADE) for dynamic model accounting the intermittent nature of solar power, randomness of load; dynamic pricing of grid and discrepancy of critical loads and choose the best possible solution for the grid outage management in the micro-grid. Furthermore, MAS improves the operating efficiency, thus maximizing the power generation of the micro-grid and minimizing the cost of operation. Thus MAS in micro-grid leads to best use of monetary and environmental resources. Simulated operation of solar generators and loads are observed by carrying out simulations under various agent objectives. Result of the simulation studies proves the efficacy of suggested outage management of the micro-grid.

Enabling Autonomic Computing Support for the JADE Agent Platform

Engineering complex distributed system is a real challenge documented in recent literature. Novel paradigms such as Autonomic Computing (AC) approaches appear to be the fittest engineering model in order to face performance instabilities of systems inserted in open and non-deterministic environments. To this purpose, the availability of appropriate development environments will facilitate the design of such systems. Standard agent development platforms represent a good starting point, but they generally lack of rigorous ways to define central AC-related concepts such as the prominent role of feedback loops and knowledge integration in decision making processes: we therefore believe that Agent Oriented Software Engineering (AOSE) can be substantially enriched by taking into account such concepts. In this paper, a novel extension of the well-known JADE agent development environment is discussed. This extension enhances JADE in order to address the engineering process with Autonomic Computing support. It is called Autonomic Computing Enabled JADE or shortly ACE-JADE. The behavioral model of ACE-JADE will be thoroughly described in the context of a case study (NASA ANTS project).

MAQ

Protected data transmission in cluster based Mobile Adhoc Networks (MANETs) is a challenging mission due to the high level of node mobility of nodes and resource constrained autonomous stations during packet routing. To target this mission, a Mobile Agent based QoS (MAQ) platform has been planned in this paper that uses an improved clustering algorithm during data communication. A Mobile agent architecture has been anticipated in a way that it is coupled with the cluster head of every cluster in MANET and when priority based real time application gets notified in these clusters then the proposed system gets activated to support prioritized service to these applications including checking and monitoring the flow characteristics for real time applications. JADE (Java Agent Development Environment) based prioritized scheme at the mobile agent has been implemented in the proposed system. As this is a function oriented approach, so the overall network performance significantly improves resulting better throughput and packet delivery ratio.

Intelligent Multi-Agent Technologies for Activating Security at Kwara State Polytechnic, Ilorin

Advancement in development of Information and Communication Technology engendered by the invention of agent technologies have fundamentally altered the ways the environment is secured. The advent of Intelligent Multi Agent technologies has also brought changes to various human activities, notably in respect of security. A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve like effective and continuous monitoring of the environment. It is observed that most institutions such as polytechnics and universities campuses are in critical positions with respect to securing of capital assets (i.e. detecting any problem through monitoring: temperature, motion, etc). Sensor networks are among the most important tools for performing such tasks. In this research work, multi agent technologies system was used to secure and/or monitor the buildings and rooms of a Polytechnic campus. The system is based on Intelligent multi agents and Wireless LAN connected sensors using JADE (Java Agent Development Environment), Netbeans and Java Development Kit (JDK).

Comparing two clustering-based techniques to track mobile nodes in industrial wireless sensor networks

Tracking mobile nodes in dynamic and noisy conditions of industrial environments has provided a paradigm for many issues inherent in the area of distributed control systems in general and wireless sensor networks in particular. Due to the dynamic nature of the industrial environments, a practical tracking system is required that is adaptable to the changes in the environment. More specifically, given the limited resources of wireless nodes and the challenges created by harsh industrial environments there is a need for a technique that can modify the configuration of the system on the fly as new wireless nodes are added to the network and obsolete ones are removed. To address these issues, two cluster-based tracking systems, one static and the other dynamic, are proposed to organize the overall network field into a set of tracking zones, each composed of a sink node and a set of corresponding anchor nodes. To manage the wireless nodes activities and inter and intra cluster communications, an agent-based technique is employed. To compare the architectures, we report on a set of experiments performed in JADE (Java Agent Development Environment). In these experiments, we compare two agent-based approaches (dynamic and static) for managing clusters of wireless sensor nodes in a distributed tracking system. The experimental results corroborate the efficiency of the static clusters versus the robustness and effectiveness of the dynamic clusters.

A Performance Evaluation of a Multi-Agent Mobile Learning System

Mobile devices have emerged as our daily companion whose applicability evolves as the day unfolds. One of such applications is in the area of learning, called mobile learning (M-learning). However, as with all new technologies, M-learning is faced with the issues of standard, content packing, and deployment. And like other distributed applications on ubiquitous networks, M-learning is challenged with performance issues. This work shows the implementation and evaluation of a model for intelligent mobile learning system (IMLS) using a multi-agent system (MAS), such as the Java Agent Development Environment (JADE) framework. Two M-learning applications (agent-based and non-agent) were developed, deployed and tested. The agent-based application is deployed using an HTTP-based Message Transfer Protocol (MTP). The results suggest that agents can increase the performance of an M-learning application up to eight times.

Autonomous Energy Management of a Micro-Grid using Multi Agent System

Multi Agent System (MAS) is a distributed system with loosely coupled agents; work together to solve problems that are beyond their individual capabilities.The objective of this paper is to implement MAS in Java Agent Development Environment (JADE) for distributed, autonomous energy management of a solar micro-grid. A grid connected solar micro-grid, which contains two solar Photo Voltaic (PV) systems, each contains a local consumer, a solar PV system and a battery, is considered. Load usage patterns and solar power generated in the two solar units are measured. Each constituents of the micro-grid is taken as an agent and these agents take decision autonomously as well as collectively for optimal energy management. The proposed approach autonomously manages the dynamics due to intermittent nature of solar power, randomness of load, dynamic pricing of grid and choose the best possible action to stabilize and optimize the solar micro-grid. MAS has the flexibility for plug and play and so solar power and load is added or removed seamlessly without affecting the micro-grid operations. Furthermore, MAS increases the operational efficiency, leading to economic and environmental optimization of solar micro-grid. All the smart grid features are implemented in the micro-grid, which is not attempted so far. The simulation outcomes demonstrate the effectiveness of proposed MAS in distributed, autonomous energy management of micro-grid, solving the constraints of using solar power. All agent actions for stabilizing the grid can be accomplished in less than ten milliseconds, taking automation of micro-grid to the next higher level.