Demand response (DR) is an effective method to lower peak-to-average ratio of demand, facilitate the integration of renewable resources (e.g., wind and solar) and plug-in hybrid electric vehicles, and strengthen the reliability of power system. In smart grid, implementing DR through home energy management system (HEMS) in residential sector has a great significance. However, an algorithm that only optimally controls parts of HEMS rather than the overall system cannot obtain the best results. In addition, single objective optimization algorithm that minimizes electricity cost cannot quantify user’s comfort level and cannot take a tradeoff between electricity cost and comfort level conveniently. To tackle these problems, this paper proposes a framework of HEMS that consists of grid, load, renewable resource (i.e., solar resource), and battery. In this framework, a user has the ability to sell electricity to utility grid for revenue. Different comfort level indicators are proposed for different home appliances according to their characteristics and user preferences. Based on these comfort level indicators, this paper proposes a multiobjective optimization algorithm for HEMS that minimizes electricity cost and maximizes user’s comfort level simultaneously. Simulation results indicate that the algorithm can reduce user’s electricity cost significantly, ensure user’s comfort level, and take a tradeoff between the cost and comfort level conveniently.
Ubiquitous light emitting dioxides provide natural infrastructures for multiuser visible light communications (VLC). The current available works mainly focus on a potential assumption of the continuous signaling. In this paper, we consider a two-user multiaccess VLC system with finite-alphabet inputs. To manage the nonnegative finite-alphabet multiuser interference, we adaptively adjust the power of each user's transmitted signals to maximize the received minimum Euclidean distance. By applying the properties of Farey sequence in number theory to solve the finite-alphabet optimization, it is proved that the optimal received signal constitutes an equally spaced pulse amplitude modulation constellation, which admits a low-complexity maximum likelihood detection. Both analytical results and computer simulations demonstrate that our proposed design has substantial performance advantage over time division multiple access, especially for significant channel strength difference.
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