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Differentiated Incentive Strategy for Demand Response in Electric Market Considering the Difference in User Response Flexibility

机译:考虑用户响应灵活性差异的电场需求响应的差异化激励策略

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摘要

In demand response programs, load service entity (LSE) can aggregate user as an independent entity to participate in the day ahead energy market, and complete the response target through incentive in the next day. In order to reduce the incentive cost of LSE, a differentiated incentive mechanism that consider the differences in user response flexibility is proposed in this paper. Then, a user response behavior model is established by using the long short-term memory (LSTM) network, with aim of accurately predicting users & x2019; response. Subsequently, an optimization strategy combining particle swarm (PSO) and LSTM is proposed, so that the response target can be accurately completed with low cost. Simulation experiments verified that the cost of LSE is close to the theoretical minimum, and can be reduced by 20 & x0025; compared with the optimal result under unified incentive mechanism. Moreover, it also verified that the proposed strategy has high response accuracy and good stability.
机译:在需求响应计划中,负载服务实体(LSE)可以将用户作为独立实体聚合,以参与前方能源市场,并在第二天通过激励完成响应目标。为了降低LSE的激励成本,在本文中提出了一种差异化的激励机制,以考虑用户响应灵活性的差异。然后,通过使用长短期存储器(LSTM)网络建立用户响应行为模型,目的是准确地预测用户和X2019;回复。随后,提出了一种组合粒子群(PSO)和LSTM的优化策略,从而可以以低成本准确地完成响应目标。仿真实验证实,LSE的成本接近理论最小值,可以减少20&x0025;与统一激励机制下的最佳结果相比。此外,它还证实了所提出的策略具有高响应准确性和良好的稳定性。

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