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Double-deck optimal schedule of micro-grid based on demand-side response

机译:基于需求侧响应的双层微电网最优调度

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摘要

In order to fully consume renewable energies and schedule demand-side resources more hierarchically, a double-deck optimal schedule model of micro-grid, which connects to power grids and concludes battery energy storage system (BESS), is proposed. Unlike the original peak-valley time-of-use (TOU) price, in the upper layer optimal schedule, the improved TOU price which takes account into the user's satisfaction can express the adjusted loads accurately and the resulting net loads can be treated as a link between upper and lower layer scheduling. For the reason of having no precise model of BESS, the lower model for the goal of minimising the operation cost is solved by action dependent heuristic dynamic programming algorithm that is not relying on the accurate controlled object model. This algorithm is used to obtain the most optimal performance index function and control strategy by the optimal iterative process, which is based on the back propagation neural network used for evaluating the optimal performance index. Analysis of examples and results has been presented to show the effectiveness of the proposed strategies.
机译:为了充分利用可再生能源并更分层地调度需求侧资源,提出了一种微电网的双层最优调度模型,该模型连接到电网并得出电池储能系统(BESS)。与最初的高峰谷使用时间(TOU)价格不同,在上层最佳计划中,考虑到用户满意度的改进的TOU价格可以准确表示调整后的负荷,并且可以将最终的净负荷视为上层和下层调度之间的链接。由于没有精确的BESS模型,因此通过不依赖于精确受控对象模型的依赖于动作的启发式动态规划算法来解决用于降低运营成本的较低模型。该算法用于通过最佳迭代过程来获得最佳性能指标函数和控制策略,该迭代过程基于用于评估最佳性能指标的反向传播神经网络。实例和结果分析已经提出来显示所提出策略的有效性。

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