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Contracting Strategy for Consumers With Distributed Energy Resources in the Liberalized Electricity Market
The rapid growth of distributed energy resources (DERs) and the new trends related to the electricity market can represent economic advantages for consumers; nevertheless, these trends can bring economic risks, such as high prices when contracting, and the inability to forecast information related t...
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Published in: | IEEE access 2022, Vol.10, p.80437-80447 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | The rapid growth of distributed energy resources (DERs) and the new trends related to the electricity market can represent economic advantages for consumers; nevertheless, these trends can bring economic risks, such as high prices when contracting, and the inability to forecast information related to offers and demand. A contracting strategy is essential to minimize possible financial losses due to consumer exposure in the liberalized electricity market. This paper proposes a contracting strategy based on consumption forecasting and a pricing methodology to optimize the contract portfolio for consumers with DERs. A consumer with a photovoltaic system and battery storage system has been considered to model the contracting strategy through a mathematical programming approach developed in four stages; the first and second stages are nonlinear programming problems, the third stage is linear programming problem, and the last stage is mixed-integer linear programming problem. The results of the case study, considering a real consumer with and without DERs, show that the strategy successfully minimized consumer exposure in the electricity market, since with operation of DERs was reduced by 45.8% the energy consumption from the main grid and by 49.7% the need for contracting, optimizing the average price of the contract portfolio and making it possible to determine an optimal contracting strategy. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2022.3194901 |