An Ontology Driven Model Approach for the Creation and Evaluation of Models in the Electricity Retail Market: A Research in Progress

Poveda, Geovanny; Schumann, René

doi:10.1109/aina.2016.135

Cited by 2 publications

(2 citation statements)

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“…The application of H-MG energy management systems with (e.g., [1,[3][4][5]) or without energy storage (ES) (e.g., [7-9, 14, 15]), and H-MGs interoperability (e.g., [10,11,16]) have been investigated in numerous research papers in the past. Developing general strategies for retail market operation have also been addressed in [17][18][19][20][21][22][23][24][25]. Colored Petri net technology [21], different game theory approaches using NIRA algorithm [22,24], Shapely value [24,26], and Cournot model [25] are among the methods which have been utilized for retail electricity market design.…”

Section: Introductionmentioning

confidence: 99%

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An advanced retail electricity market for active distribution systems and home microgrid interoperability based on game theory

Marzband

Javadi

Pourmousavi

et al. 2018

Electric Power Systems Research

105

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The concept of active distribution network has emerged by the application of new generation and storage technologies, demand flexibility, and communication infrastructure. The main goal is to create infrastructure and algorithms to facilitate an increased penetration of distributed energy resources, application of demand response and storage technologies, and encourage local generation and consumption within the distribution network. However, managing thousands of prosumers with different requirements and objectives is a challenging task. To do so, market mechanisms are found to be necessary to fully exploit the potential of customers, known as Prosumers in this new era. This paper offers an advanced retail electricity market based on game theory for the optimal operation of home microgrids (H-MGs) and their interoperability within active distribution networks. The proposed market accommodates any number of retailers and prosumers incorporating different generation sources, storage devices, retailers, and demand response resources. It

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Section: Introductionmentioning

confidence: 99%

“…• No solution is proposed to guarantee the benefit of all players with competing objectives in a multiple ownership environment in [15-17, 21, 30, 31] while the proposed solutions in [18,19,25,28,29] do not guarantee the optimality of the final solution.…”

Section: Introductionmentioning

confidence: 99%