Robust optimisation approach for bidding strategy of renewable generation-based microgrid under demand side management

In the restructured electricity market, operator of grid-connected microgrid (MG) tries to supply local load at the lowest cost from alternative energy sources including upstream grid, gas-turbines as local dispatchable units and renewable energy sources (photovoltaic systems and wind-turbines) as w...

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Bibliographic Details
Published in:IET renewable power generation Vol. 11; no. 11; pp. 1446 - 1455
Main Authors: Mehdizadeh, Ali, Taghizadegan, Navid
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 13.09.2017
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ISSN:1752-1416, 1752-1424, 1752-1424
Online Access:Get full text
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Summary:In the restructured electricity market, operator of grid-connected microgrid (MG) tries to supply local load at the lowest cost from alternative energy sources including upstream grid, gas-turbines as local dispatchable units and renewable energy sources (photovoltaic systems and wind-turbines) as well as charge/discharge of energy storage system. In order to purchase power from upstream grid, the bidding curve of MG should be prepared to bid to the market operator. Therefore, this study proposes a robust optimisation approach (ROA) for obtaining optimal bidding strategy of MG. Also, MG operator uses time-of-use rate of demand response program (DRP) to reduce procurement energy cost. For this purpose, ROA is used for uncertainty modelling of upstream grid prices in which the minimum and maximum limits of prices are considered for the uncertainty modelling. The lower and upper bounds of price are consecutively subdivided into sequentially nested subintervals which allow formulating robust mixed-integer linear programming problems. The bidding strategy curves of MG for each time considering DRP are obtained from sufficient data by solving these problems. To show the capability of proposed approach, two cases are studied.
ISSN:1752-1416
1752-1424
1752-1424
DOI:10.1049/iet-rpg.2017.0076