Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based Implementation
This paper proposes a novel framework for conducting sealed-bid double auctions in power trading for multi-microgrid networks, addressing the critical challenge of jointly optimizing bidding decisions and battery scheduling under uncertainty in renewable energy generation and load demand. In contras...
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| Format: | Article |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11072108/ |
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| author | Zubin J. B. Sunitha R. Gopakumar Pathirikkat |
| author_facet | Zubin J. B. Sunitha R. Gopakumar Pathirikkat |
| author_sort | Zubin J. B. |
| collection | DOAJ |
| description | This paper proposes a novel framework for conducting sealed-bid double auctions in power trading for multi-microgrid networks, addressing the critical challenge of jointly optimizing bidding decisions and battery scheduling under uncertainty in renewable energy generation and load demand. In contrast to existing approaches that treat these components independently, our method explicitly models their interdependency for maximizing trading efficiency. We assume a normal distribution of prediction errors and introduce an uncertainty range and a bid buffer capacity to account for expected variations in forecasted generation and load, enabling more robust coordination between bidding and storage operations. While Q-learning determines the exact bid, the feasible power availability or demand is derived from the uncertainty range, ensuring consistency between learned bidding decisions and forecast-aware constraints. The Q-learning relies solely on its historical bidding outcomes without attempting to predict the bids of other participants. In parallel, battery operations are optimized using a hybrid method that combines Genetic Algorithm (GA) and Simulated Annealing (SA), explicitly incorporating the bid buffer capacity to align scheduling with market commitments. We also propose a fully decentralized and tamper-resistant execution architecture based on a consortium blockchain, where multiple aggregator agents within each microgrid, representing renewable sources, loads, storage systems, and the bid agent, function as independent blockchain nodes. Simulation results on a benchmark microgrid system with Monte-Carlo modeled prediction errors demonstrate that the proposed approach significantly enhances both economic benefits and trading robustness compared to conventional frameworks. |
| format | Article |
| id | doaj-art-7a03707d3f6e4dc5b36a0980004eafde |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-7a03707d3f6e4dc5b36a0980004eafde2025-08-20T03:50:21ZengIEEEIEEE Access2169-35362025-01-011311795311797010.1109/ACCESS.2025.358646511072108Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based ImplementationZubin J. B.0https://orcid.org/0000-0001-6750-5503Sunitha R.1https://orcid.org/0000-0002-4247-4998Gopakumar Pathirikkat2https://orcid.org/0000-0002-9018-9446Electrical Engineering Department, National Institute of Technology Calicut, Kozhikode, IndiaElectrical Engineering Department, National Institute of Technology Calicut, Kozhikode, IndiaElectrical Engineering Department, National Institute of Technology Calicut, Kozhikode, IndiaThis paper proposes a novel framework for conducting sealed-bid double auctions in power trading for multi-microgrid networks, addressing the critical challenge of jointly optimizing bidding decisions and battery scheduling under uncertainty in renewable energy generation and load demand. In contrast to existing approaches that treat these components independently, our method explicitly models their interdependency for maximizing trading efficiency. We assume a normal distribution of prediction errors and introduce an uncertainty range and a bid buffer capacity to account for expected variations in forecasted generation and load, enabling more robust coordination between bidding and storage operations. While Q-learning determines the exact bid, the feasible power availability or demand is derived from the uncertainty range, ensuring consistency between learned bidding decisions and forecast-aware constraints. The Q-learning relies solely on its historical bidding outcomes without attempting to predict the bids of other participants. In parallel, battery operations are optimized using a hybrid method that combines Genetic Algorithm (GA) and Simulated Annealing (SA), explicitly incorporating the bid buffer capacity to align scheduling with market commitments. We also propose a fully decentralized and tamper-resistant execution architecture based on a consortium blockchain, where multiple aggregator agents within each microgrid, representing renewable sources, loads, storage systems, and the bid agent, function as independent blockchain nodes. Simulation results on a benchmark microgrid system with Monte-Carlo modeled prediction errors demonstrate that the proposed approach significantly enhances both economic benefits and trading robustness compared to conventional frameworks.https://ieeexplore.ieee.org/document/11072108/Microgrid networkpower tradingstrategic bidbattery schedulinguncertaintyblockchain |
| spellingShingle | Zubin J. B. Sunitha R. Gopakumar Pathirikkat Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based Implementation IEEE Access Microgrid network power trading strategic bid battery scheduling uncertainty blockchain |
| title | Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based Implementation |
| title_full | Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based Implementation |
| title_fullStr | Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based Implementation |
| title_full_unstemmed | Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based Implementation |
| title_short | Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based Implementation |
| title_sort | integrated bidding and battery scheduling in a microgrid for sealed bid double auction power trading with peer microgrids under uncertainty and its blockchain based implementation |
| topic | Microgrid network power trading strategic bid battery scheduling uncertainty blockchain |
| url | https://ieeexplore.ieee.org/document/11072108/ |
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