Optimal Energy Scheduling for Residential Smart Grid With Centralized Renewable Energy Source

Optimal Energy Scheduling for Residential Smart Grid With Centralized Renewable Energy Source
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DOI:
10.1109/jsyst.2013.2261001
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发表时间:
2014-06
影响因子:
4.4
通讯作者:
Yuan Wu;V. Lau;D. Tsang;L. Qian;L. Meng
Yuan Wu;V. Lau;D. Tsang;L. Qian;L. Meng
中科院分区:
计算机科学2区
文献类型:
--
作者:
Yuan Wu;V. Lau;D. Tsang;L. Qian;L. Meng

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未来的智能电网将以灵活的供需管理和可再生能源的大力渗透为特色,以实现高效和经济的电网运营。虽然可再生能源提供了更便宜和更清洁的能源供应,但由于可再生能源的波动性,它引入了供应的不确定性。因此,研究基于未来智能电网供需框架的可再生能源的优化利用具有重要的现实意义,其中能源供应商(或能源用户)根据考虑可再生能源波动性的系统状态信息自适应地调整其能源供应(或能源需求)。具体来说,我们认为具有成本效益的能源调度的住宅智能电网配备了一个集中的可再生能源。我们的调度问题的目的是:1)量化可再生能源的最佳利用,实现系统范围内的利益之间的权衡,从利用可再生能源和相关的成本,由于其波动性;和2)评估可再生能源的波动性如何影响其最佳利用。我们还提出了计算效率和分布式算法,以确定可再生能源的最佳利用以及相关的能源调度决策。
Future smart grids will be featured by flexible supply-demand management and great penetration of renewable energy to enable efficient and economical grid operations. While the renewable energy offers a cheaper and cleaner energy supply, it introduces supply uncertainty due to the volatility of renewable source. It is therefore of practical importance to investigate the optimal exploitation of renewable energy based on the supply-demand framework of future smart grids, where the energy-providers (or the energy-users) adaptively adjust their energy-provisioning (or energy-demands) according to some system state information that takes into account the volatility of renewable energy. Specifically, we consider cost-efficient energy scheduling for residential smart grids equipped with a centralized renewable energy source. Our scheduling problem aims at: 1) quantifying the optimal utilization of renewable energy that achieves the tradeoff between the system-wide benefit from exploiting the renewable energy and the associated cost due to its volatility; and 2) evaluating how the volatility of renewable energy influences its optimal exploitation. We also propose computationally efficient and distributed algorithms to determine the optimal exploitation of renewable energy as well as the associated energy scheduling decisions.