Intelligent Energy Control Center for Distributed Generators Using Multi-Agent System

Manickavasagam, Krishnan

doi:10.1109/tpwrs.2014.2368592

Cited by 32 publications

(8 citation statements)

References 12 publications

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“…One is based on centralized control [9][10][11][12][13], while the other is based on distributed control [14][15][16][17][18][19][20][21][22][23][24][25][26][27]. In order to dispatch the power optimally, in [9][10][11][12], the authors use a centralized controller to make the decisions for generating the optimal power generation commands based on the generation cost.…”

Section: Introductionmentioning

confidence: 99%

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Operation Cost Minimization of Droop-Controlled AC Microgrids Using Multiagent-Based Distributed Control

Savaghebi

Guerrero

et al. 2016

Energies

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Abstract:Recently, microgrids are attracting increasing research interest as promising technologies to integrate renewable energy resources into the distribution system. Although many works have been done on droop control applied to microgrids, they mainly focus on achieving proportional power sharing based on the power rating of the power converters. With various primary source for the distributed generator (DG), factors that are closely related to the operation cost, such as fuel cost of the generators and losses should be taken into account in order to improve the efficiency of the whole system. In this paper, a multiagent-based distributed method is proposed to minimize the operation cost in AC microgrids. In the microgrid, each DG is acting as an agent which regulates the power individually using a novel power regulation method based on frequency scheduling. An optimal power command is obtained through carefully designed consensus algorithm by using sparse communication links only among neighbouring agents. Experimental results for different cases verified that the proposed control strategy can effectively reduce the operation cost.

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Section: Introductionmentioning

confidence: 99%

“…Each agent has the properties of autonomy, reactivity, pro-activeness and social ability [16][17][18][19][20][21][22][23][24][25][26][27], and they exchange information with the corresponding agent to make the decisions locally for collaborative purposes. There are mainly two concepts that can be applied to form a multiagent platform.…”

Section: Introductionmentioning

confidence: 99%

Operation Cost Minimization of Droop-Controlled AC Microgrids Using Multiagent-Based Distributed Control

Savaghebi

Guerrero

et al. 2016

Energies

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“…In each area, we chose an agent that is responsible for coordinating the distributed devices within the region. These agents can be divided according to the control scope or the control functions [72,73]. The scheduler does not directly control the distributed device, but only issues scheduling instructions to the agent.…”

mentioning

confidence: 99%

Blockchain Technology for Information Security of the Energy Internet: Fundamentals, Features, Strategy and Application

Zeng

Cao

et al. 2020

Energies

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In order to ensure the information security, most of the important information including the data of advanced metering infrastructure (AMI) in the energy internet is currently transmitted and exchanged through the intranet or the carrier communication. The former increases the cost of network construction, and the latter is susceptible to interference and attacks in the process of information dissemination. The blockchain is an emerging decentralized architecture and distributed computing paradigm. Under the premise that these nodes do not need mutual trust, the blockchain can implement trusted peer-to-peer communication for protecting the important information by adopting distributed consensus mechanisms, encryption algorithms, point-to-point transmission and smart contracts. In response to the above issues, this paper firstly analyzes the information security problems existing in the energy internet from the four perspectives of system control layer, device access, market transaction and user privacy. Then blockchain technology is introduced, and its working principles and technical characteristics are analyzed. Based on the technical characteristics, we propose the multilevel and multichain information transmission model for the weak centralization of scheduling and the decentralization of transaction. Furthermore, we discuss that the information transmission model helps solve some of the information security issues from the four perspectives of system control, device access, market transaction and user privacy. Application examples are used to illustrate the technical features that benefited from the blockchain for the information security of the energy internet.

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“…4.1.5 Solar power generation:The solar PV cells are connected in series to form a solar panel. Typically, 36 solar cells are connected to develop 21.6 V as in[14]. To generate 220 V DC supply, ∼11 modules are connected.…”

mentioning

confidence: 99%

Intelligent energy management system for renewable energy driven ship

Manickavasagam

Thotakanama

Puttaraj

2019

IET Electrical Systems in Transportation

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Utilisation of renewable energy sources (RES) is increasing day by day to reduce greenhouse emissions. The toxic emission from ship is the main concern in marine sector. Here, utilisation of renewable energy for propulsion and electrification of accessories in a ship are proposed. Microgrid with AC and DC bus is developed using solar panels, wind mills, fuel cell, diesel generator, and energy storage devices. Energy management system with two fuzzy logic controllers (FLCs) is used to select and manage energy in the microgrid. Selection of source is decided by FLC1 based on the availability of RES. Generation of control pulses for inter-linking converters is decided by FLC2 based on variation in solar irradiance and wind velocity. The microgrid with RES is simulated using MATLAB/SIMULINK. The results show that uncertainty in RES can be handled by FLCs to provide a continuous power supply for transportation of ship and its accessories. 2 Description of the system 2.1 Implementation of EMS The proposed system consists of EMS, microgrid with AC and DC bus, solar power generation, wind power generation, ESD, diesel

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Intelligent Energy Control Center for Distributed Generators Using Multi-Agent System

Cited by 32 publications

References 12 publications

Operation Cost Minimization of Droop-Controlled AC Microgrids Using Multiagent-Based Distributed Control

Operation Cost Minimization of Droop-Controlled AC Microgrids Using Multiagent-Based Distributed Control

Blockchain Technology for Information Security of the Energy Internet: Fundamentals, Features, Strategy and Application

Intelligent energy management system for renewable energy driven ship

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