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Decentralized Coordination of Energy Utilization for Residential Households in the Smart Grid

机译:智能电网中居民家庭能源利用的分散协调

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摘要

In this paper, we investigate the minimization of the total energy cost of multiple residential households in a smart grid neighborhood sharing a load serving entity. Specifically, each household may have renewable generation, energy storage as well as inelastic and elastic energy loads, and the load serving entity attempts to coordinate the energy consumption of these households in order to minimize the total energy cost within this neighborhood. The renewable generation, the energy demand arrival, and the energy cost function are all stochastic processes and evolve according to some, possibly unknown, probabilistic laws. We develop an online control algorithm, called Lyapunov-based cost minimization algorithm (LCMA), which jointly considers the energy management and demand management decisions. LCMA only needs to keep track of the current values of the underlying stochastic processes without requiring any knowledge of their statistics. Moreover, a decentralized algorithm to implement LCMA is also developed, which can preserve the privacy of individual household owners. Numerical results based on real-world trace data show that our control algorithm can effectively reduce the total energy cost in the neighborhood.
机译:在本文中,我们研究了共享负载服务实体的智能电网社区中多个居民家庭的总能源成本的最小化。具体而言,每个家庭可能具有可再生能源发电,能量存储以及非弹性和弹性能源负荷,并且负荷服务实体试图协调这些家庭的能源消耗,以使该邻域内的总能源成本最小化。可再生能源发电,能源需求的到来以及能源成本函数都是随机过程,并根据一些可能未知的概率定律演化。我们开发了一种在线控制算法,称为基于Lyapunov的成本最小化算法(LCMA),该算法共同考虑了能源管理和需求管理决策。 LCMA只需要跟踪基础随机过程的当前值,而无需了解其统计信息。此外,还开发了一种实现LCMA的分散算法,该算法可以保护单个家庭所有者的隐私。基于真实世界跟踪数据的数值结果表明,我们的控制算法可以有效降低附近地区的总能源成本。

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