Hardware-in-the-Loop Simulation of Distributed Intelligent Energy Management System for Microgrids

Oh, Sang-Jin; Yoo, Cheol-Hee; Chung, Ilyong; Won, Dong-Jun

doi:10.3390/en6073263

Cited by 23 publications

(14 citation statements)

References 16 publications

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“…Figure 8 shows the construction of the HILS test system with the MGCC program and agents. In this study, the MGCC program is used for monitoring and managing this system, and the agents of the BESS and load were constructed to verify the performance of the proposed algorithm and simulate the microgrid operation [15]. The following describes each component of the system.…”

Section: Start (T=0)mentioning

confidence: 99%

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

et al. 2015

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Abstract:The microgrid and demand response (DR) are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS) has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS) and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC) through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR). The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.

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Section: Start (T=0)mentioning

confidence: 99%

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

et al. 2015

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“…Both references apply the concept of the Contract Net Protocol (CNP) for the decision-making procedure. In our previous research, we also applied microgrid energy management schemes using MAS with CNP and also implemented a hardware-in-the-loop simulation system for experimental verification [17,18]. In this paper, we present improved intelligent control schemes for BESS agents using state machine concept and fuzzy-logic charging/discharging algorithms in order to participate in the IDRP of KPX.…”

Section: Multi-agent Based Microgrid Energy Managementmentioning

confidence: 99%

Intelligent Control of Battery Energy Storage for Multi-Agent Based Microgrid Energy Management

et al. 2013

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Microgrids can be considered as controllable units from the utility point of view because the entities of microgrids such as distributed energy resources and controllable loads can effectively control the amount of power consumption or generation. Therefore, microgrids can make various contracts with utility companies such as demand response program or ancillary services. Another advantage of microgrids is to integrate renewable energy resources to low-voltage distribution networks. Battery energy storage systems (BESSs) can effectively compensate the intermittent output of renewable energy resources. This paper presents intelligent control schemes for BESSs and autonomous energy management schemes of microgrids based on the concept of multi-agent systems. The proposed control scheme consists of two layers of decision-making procedures. In the bottom layer, intelligent agents decide the optimal operation strategies of individual microgrid entities such as BESSs, backup generators and loads. In the upper layer, the central microgrid coordinator (MGCC) coordinates multiple agents so that the overall microgrid can match the load reduction requested by the grid operator. The proposed control scheme is applied to Korea Power Exchange's Intelligent Demand Response Program.

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“…Power Hardware in the Loop (PHIL) [1] is a real-time simulation technology that is widely used in power systems for facility testing and validation [2][3][4][5][6]. A general architecture of a PHIL system is shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

A Stable and Fast-Transient Performance Switched-Mode Power Amplifier for a Power Hardware in the Loop (PHIL) System

Sun

Yin²,

Gong

et al. 2017

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Power Hardware in the Loop (PHIL) systems are used to test a power system with the help of combined software and hardware. Generally, to construct a PHIL system, a switched-mode power amplifier that has a stable performance is used, because of their large, linear signal control-to-output characteristics. However, the fundamental limitations of a switch-mode power amplifier (PA) are the dynamic performance and output bandwidth. In this paper, a compound controller has been used for the rectifier part of a PA, which can ensure the stability of a PA under transient or fault operating conditions. Moreover, a compound controller, which involves a feed-forward controller, a proportional controller and a repetitive controller, is proposed in the inverter part of a PA, and it can be used for PHIL applications. Experimental results are obtained under various operating conditions, such as transient responses under load step change, and output voltage bandwidth testing for a PHIL system, it is concluded that a proposed switched-mode power amplifier is useful for the PHIL system.

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Hardware-in-the-Loop Simulation of Distributed Intelligent Energy Management System for Microgrids

Cited by 23 publications

References 16 publications

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

Intelligent Control of Battery Energy Storage for Multi-Agent Based Microgrid Energy Management

A Stable and Fast-Transient Performance Switched-Mode Power Amplifier for a Power Hardware in the Loop (PHIL) System

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