Simulation system for the coordination of decentralized energy conversion plants on basis of a distributed data base system

Handschin, E.; Uphaus, Frank

doi:10.1109/ptc.2005.4524428

Cited by 8 publications

(4 citation statements)

References 1 publication

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“…The methodology is based on a cost function for every device and using a Non Linear Problem definition the optimal schedule is found. The authors of [19] address the problems of both agent and non-agent based solutions: non-agent based solution are less scalable and agent based solutions need local intelligence and are not transparent. Therefore, they propose a combination: aggregate data on multiple levels, while these levels contain some intelligence.…”

Section: Related Workmentioning

confidence: 99%

Management and Control of Domestic Smart Grid Technology

Molderink

Bakker

Bosman

et al. 2010

IEEE Trans. Smart Grid

537

288

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Emerging new technologies like distributed generation, distributed storage, and demand side load management will change the way we consume and produce energy. These techniques enable the possibility to reduce the greenhouse effect and improve grid stability by optimizing energy streams. By smartly applying future energy production, consumption and storage techniques, a more energy efficient electricity supply chain can be achieved. In this paper a three-step control methodology is proposed to manage the cooperation between these technologies, focused on domestic energy streams. In this approach, (global) objectives like peak shaving or forming a Virtual Power Plant can be achieved without harming the comfort of residents. As shown in this work, using good predictions, in advance planning and realtime control of domestic appliances, a better matching of demand and supply can be achieved.

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Section: Related Workmentioning

confidence: 99%

Management and Control of Domestic Smart Grid Technology

Molderink

Bakker

Bosman

et al. 2010

IEEE Trans. Smart Grid

537

288

View full text Add to dashboard Cite

show abstract

“…Several VPP control algorithms have been proposed for different purposes [37][38][39][40][41]. The goal of the VPP designed for the HABVIP controller is to obtain constant power output.…”

Section: Smart Micro-chp Controlmentioning

confidence: 99%

Coordinated agent-based control for online voltage instability prevention

Baalbergen

2013

Int. Trans. Electr. Energ. Syst.

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SUMMARY In this paper, a new method for online voltage instability control suitable for smart grid application is proposed. The method uses the Maximum Loadability Index to determine the amount of load relief necessary to restore stability. This measure can be determined based on local measurements. The load relief is obtained by: increase of local generation, virtual load shedding via adjusting the Load Tap Changers (LTCs) set‐point, intelligent load control and the increase of reactive power compensation from Static Var Compensators. For the local generation, the control of two types is described: for micro Combined Heat and Power (micro‐CHP) units and for large synchronous generators. In order to obtain constant power supply from a group of micro‐CHPs, a Virtual Power Plant coordination method is proposed. The control of the actuators is outlined, and a method is described to coordinate their actions. Based on simulations it is demonstrated that the proposed method works properly: voltage collapse can be avoided, and voltage stability is restored. A sensitivity analysis is performed to determine the optimal settings of the coordinated controller. Furthermore, the merit of including reactive power control in the proposed control strategy is investigated. Compared to classical controls, such as Under‐Voltage Load Shedding and LTCs tap blocking, the method performs better. Copyright © 2013 John Wiley & Sons, Ltd.

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“…Using a Non Linear Problem definition the optimal on/off switch pattern is found. The authors of [22] address the problems of both agent and non-agent based solutions: non-agent based solution are less scalable and agent based solutions need local intelligence and are not transparent. Therefore, they propose a combination: aggregate data on multiple levels, while these levels contain some intelligence.…”

Section: Related Workmentioning

confidence: 99%

A three-step methodology to improve domestic energy efficiency

Molderink

Bakker

Bosman

et al. 2010

2010 Innovative Smart Grid Technologies (ISGT)

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Abstract-Increasing energy prices and the greenhouse effect lead to more awareness of energy efficiency of electricity supply. During the last years, a lot of technologies have been developed to improve this efficiency. Next to large scale technologies such as windturbine parks, domestic technologies are developed. These domestic technologies can be divided in 1) Distributed Generation (DG), 2) Energy Storage and 3) Demand Side Load Management. Control algorithms optimizing a combination of these techniques can raise the energy reduction potential of the individual techniques. In this paper an overview of current research is given and a general concept is deducted. Based on this concept, a three-step optimization methodology is proposed using 1) offline local prediction, 2) offline global planning and 3) online local scheduling. The paper ends with results of simulations and field tests showing that the methodology is promising.

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Simulation system for the coordination of decentralized energy conversion plants on basis of a distributed data base system

Cited by 8 publications

References 1 publication

Management and Control of Domestic Smart Grid Technology

Management and Control of Domestic Smart Grid Technology

Coordinated agent-based control for online voltage instability prevention

A three-step methodology to improve domestic energy efficiency

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