Journal
IEEE TRANSACTIONS ON SMART GRID
Volume 4, Issue 3, Pages 1341-1350Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2013.2268581
Keywords
Demand response; energy management; energy storage; inelastic and elastic energy loads; Lyapunov optimization; renewable generation; smart grid
Categories
Funding
- U.S. National Science Foundation [CNS-1147813, ECCS-1129061, ECCS-1129062]
- University of Florida
- Directorate For Engineering [1723849] Funding Source: National Science Foundation
- Directorate For Engineering
- Div Of Electrical, Commun & Cyber Sys [1129061] Funding Source: National Science Foundation
- Div Of Electrical, Commun & Cyber Sys [1723849] Funding Source: National Science Foundation
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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.
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