- Title
- Market model for clustered microgrids optimisation including distribution network operations
- Creator
- Batool, Munira; Islam, Syed; Shahnia, Farhad
- Date
- 2019
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/170956
- Identifier
- vital:14217
- Identifier
- 10.1049/iet-gtd.2018.5275
- Identifier
- ISBN:1751-8687
- Abstract
- This paper proposes a market model for the purpose of optimisation of clustered but sparse microgrids (MGs). The MGs are connected with the market by distribution networks for the sake of energy balance and to overcome emergency situations. The developed market structure enables the integration of virtual power plants (VPPs) in energy requirement of MGs. The MGs, internal service providers (ISPs), VPPs and distribution network operator (DNO) are present as distinct entities with individual objective of minimum operational cost. Each MG is assumed to be present with a commitment to service its own loads prior to export. Thus an optimisation problem is formulated with the core objective of minimum cost of operation, reduced network loss and least DNO charges. The formulated problem is solved by using heuristic optimization technique of Genetic Algorithm. Case studies are carried out on a distribution system with multiple MGs, ISP and VPPs which illustrates the effectiveness of the proposed market optimisation strategy. The key objective of the proposed market model is to coordinate the operation of MGs with the requirements of the market with the help of the DNO, without decreasing the economic efficiency for the MGs nor the distribution network. © The Institution of Engineering and Technology 2019.
- Publisher
- Institution of Engineering and Technology
- Relation
- IET Generation, Transmission and Distribution Vol. 13, no. 22 (2019), p. 5139-5150
- Rights
- © The Institution of Engineering and Technology 2019
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0906 Electrical and Electronic Engineering; Distributed power generation; Genetic algorithms; Power generation dispatch; Power distribution economics
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