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- W4360995639 abstract "The paper proposes a demand-side response crowd-Sourcing model, combining crowdSourcing and demand-side response and providing a smooth channel to help demand-side users participate in electric market transactions. The model reduces the uncertainty of the users' behavior and is conductive to maintain the balance of power supply and demand. Considering the influence of subsidies on demand-side users' willingness to participate in electricity market transactions, the paper supposed an improved multi-objective particle swarm optimization algorithm to calculate electricity market transaction crowdsourcing task subsidy allocation scheme, successfully improving the completion rate of demand-side response crowdsourcing tasks in the dataset by 25.4% and the high-quality task completion rate by 30.0%. Compared with other algorithms, the convergence speed of this algorithm is also faster." @default.
- W4360995639 created "2023-03-30" @default.
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- W4360995639 date "2022-12-23" @default.
- W4360995639 modified "2023-09-24" @default.
- W4360995639 title "Demand-Side Response Crowdsourcing Model and Its Subsidy Allocation Optimization Method" @default.
- W4360995639 doi "https://doi.org/10.1109/icpes56491.2022.10072440" @default.
- W4360995639 hasPublicationYear "2022" @default.
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